Warehouse planning method and warehouse planning device

Abstract

The invention relates to the technical field of warehouse logistics, and discloses a warehouse planning method and a warehouse planning device, and the method comprises the steps: obtaining a to-be-processed task inputted by a user in a user interaction interface; splitting the to-be-processed task through the storage planning model to obtain at least one subtask; analyzing and processing each sub-task through the storage planning model to obtain at least one piece of request information corresponding to each sub-task, and controlling a user interaction interface to display each piece of request information; in response to at least one piece of feedback information input by the user for the at least one piece of request information corresponding to each sub-task, determining a processing result corresponding to each sub-task through a storage planning model; and based on the processing result corresponding to each sub-task in the at least one sub-task, determining a planning result corresponding to the to-be-processed task through a storage planning model. According to the invention, the project information of the user is collected through an interaction mode, the planning of the warehousing system is realized according to the collected project information, and the planning efficiency of the warehousing system is improved.

Description

Technical Field

[0001] The present application relates to the technical field of warehousing logistics, and in particular to a warehousing planning method and a warehousing planning device. Background Art

[0002] Before deploying a warehousing system, users may want to know the deployment plan of the warehousing system in advance to determine whether the deployment plan meets their needs. Therefore, the planners of the warehousing system can understand the project parameters of the user's warehousing system and user needs, and after collecting relevant information, determine the warehousing deployment plan based on the collected information. However, the process of collecting information on the warehousing system and determining the warehousing deployment plan may require a lot of time and manpower costs, resulting in low efficiency and high cost of warehousing system deployment. Summary of the invention

[0003] In order to solve the above problems, the embodiments of the present application provide a warehouse planning method and a warehouse planning device, which can improve the planning efficiency of the warehouse system and reduce the manpower cost of planning. Specifically, the embodiments of the present application disclose the following technical solutions:

[0004] The first aspect of an embodiment of the present application provides a warehouse planning method, which includes: first, obtaining a pending task input by a user in a user interaction interface. Then, splitting and processing the pending task through a warehouse planning model to obtain at least one subtask. Secondly, analyzing and processing each subtask through the warehouse planning model to obtain at least one request information corresponding to each subtask, and controlling the user interaction interface to display each request information. Thirdly, in response to at least one feedback information input by the user for at least one request information corresponding to each subtask, determining the processing result corresponding to each subtask through the warehouse planning model. Finally, based on the processing result corresponding to each subtask in at least one subtask, determine the planning result corresponding to the pending task through the warehouse planning model, and control the user interaction interface to display the planning result.

[0005] In some embodiments, the warehouse planning model includes a task splitting sub-model, which splits the task to be processed through the warehouse planning model to obtain at least one sub-task, including: based on the complexity of the task to be processed and a preset splitting principle, splitting the task to be processed into at least one sub-task through the task splitting sub-model; wherein the preset splitting principle includes that the number of tasks of at least one sub-task is less than or equal to a preset number threshold and / or the correlation between any two sub-tasks in the at least one sub-task is less than or equal to a preset correlation threshold.

[0006] In some embodiments, the warehouse planning model includes a task execution sub-model, which analyzes and processes each sub-task through the warehouse planning model to obtain at least one request information corresponding to each sub-task, and controls the user interaction interface to display each request information, including: analyzing and processing the first sub-task based on the task execution sub-model, determining the first request information corresponding to the first sub-task, and controlling the user interaction interface to display the first request information; wherein, at least one sub-task includes a first sub-task, and at least one request information corresponding to the first sub-task includes the first request information.

[0007] In some embodiments, in response to at least one feedback information input by the user for at least one request information corresponding to each subtask, the processing result corresponding to each subtask is determined through the warehouse planning model, including: in response to first feedback information input by the user for first request information corresponding to the first subtask, second request information corresponding to the first subtask is determined through the task execution submodel, and the user interaction interface is controlled to display the second request information; wherein the at least one request information corresponding to the first subtask includes the second request information; in response to second feedback information input by the user for the second request information, the first processing result corresponding to the first subtask is determined through the task execution submodel based on the first feedback information and the second feedback information.

[0008] In some embodiments, at least one subtask includes a first subtask and a second subtask, and the second subtask is the next task of the first subtask; after determining a first processing result corresponding to the first subtask, in response to at least one feedback information input by the user for at least one request information corresponding to each subtask, the processing result corresponding to each subtask is determined through a warehouse planning model, including: based on the at least one feedback information corresponding to the first subtask, analyzing and processing the second subtask through the warehouse planning model, determining at least one request information corresponding to the second subtask, and controlling the user interaction interface to display at least one request information corresponding to the second subtask; in response to at least one feedback information input by the user for at least one request information corresponding to the second subtask, determining a second processing result corresponding to the second subtask through the warehouse planning model.

[0009] In some embodiments, based on at least one feedback information corresponding to the first subtask, the second subtask is analyzed and processed through the warehouse planning model to determine at least one request information corresponding to the second subtask, and the user interaction interface is controlled to display the at least one request information corresponding to the second subtask, including: analyzing and processing the second subtask through the task execution submodel to obtain at least one request information corresponding to the second subtask; wherein, the at least one request information corresponding to the second subtask includes third request information and fourth request information; if there is feedback information corresponding to the third request information in the at least one feedback information corresponding to the first subtask, and there is no feedback information corresponding to the fourth request information in the at least one feedback information corresponding to the first subtask, then the user interaction interface is controlled not to display the third request information and to display the fourth request information; if there is no feedback information corresponding to the third request information in the at least one feedback information corresponding to the first subtask, then the user interaction interface is controlled to display the third request information.

[0010] In some embodiments, based on the processing results corresponding to each subtask in at least one subtask, the planning results corresponding to the task to be processed are determined through the warehouse planning model, and the user interaction interface is controlled to display the planning results, including: based on the first processing result and the second processing result, the planning results corresponding to the task to be processed are determined through the task execution submodel, and the user interaction interface is controlled to display the planning results.

[0011] In some embodiments, the warehouse planning model includes a task execution sub-model, which includes a first execution network and a second execution network; in response to at least one feedback information input by a user for the at least one request information corresponding to each sub-task, the processing result corresponding to each sub-task is determined through the warehouse planning model, including: determining the task objective and preset algorithm library of the sub-task; based on the task objective of the sub-task, the preset algorithm library, and at least one feedback information corresponding to the sub-task, determining the task execution information corresponding to the sub-task through the first execution network; wherein the task execution information is used to indicate a target execution method for achieving the task objective of the sub-task; the preset algorithm library includes multiple algorithms, and the target execution method includes calling at least one algorithm in the preset algorithm library; based on the task execution information, determining the processing result corresponding to the sub-task through the second execution network.

[0012] In some embodiments, the task objective of the subtask includes determining an efficiency index of the warehousing system, and the target execution method includes calling an efficiency prediction model in a preset algorithm library.

[0013] In some embodiments, based on the task execution information, the processing result corresponding to the subtask is determined through the second execution network, including: based on the task execution information and at least one feedback information corresponding to the subtask, the efficiency prediction model is called through the second execution network to generate the processing result corresponding to the subtask; wherein the processing result includes multiple groups of prediction information, and the multiple groups of prediction information are used to indicate the efficiency indicators corresponding to multiple groups of system parameters in the warehousing system.

[0014] In some embodiments, the efficiency prediction model includes a first prediction sub-model and a second prediction sub-model; based on the task execution information and at least one feedback information corresponding to the sub-task, the efficiency prediction model is called through the second execution network to generate a processing result corresponding to the sub-task, including: based on the at least one feedback information corresponding to the sub-task, the target input information is determined; wherein the target input information includes the warehouse size, handling equipment type and carrier handling efficiency corresponding to the warehousing system; based on the first prediction sub-model, the target input information is processed to obtain the target configuration parameters of the warehousing system; wherein the target configuration parameters include the number of handling equipment and / or the number of workstations; the target configuration parameters are similarly processed by a preset similarity algorithm to expand to obtain multiple groups of system configuration parameters; wherein the multiple groups of system configuration parameters include the target configuration parameters; based on the second prediction sub-model, the multiple groups of system configuration parameters are processed to determine the efficiency indicators corresponding to each group of system configuration parameters; wherein the efficiency indicators include at least one of the workstation utilization rate, handling equipment utilization rate, task cycle time and number of vehicles of the warehousing system.

[0015] In some embodiments, at least one subtask includes a first subtask and a second subtask, and the second subtask is the next subtask of the first subtask; the warehouse planning model includes a task execution submodel and a task correction submodel, and the method also includes: if the first processing result corresponding to the first subtask cannot be determined through the task execution submodel, or if the first processing result corresponding to the first subtask is determined to be abnormal through the task execution submodel, then the first subtask is optimized through the task correction submodel to obtain an optimized first subtask; wherein the optimization includes further splitting the first subtask, or adjusting the first subtask to re-determine at least one request information corresponding to the optimized first subtask through the task execution submodel; if the confirmation information input by the user on the user interaction interface for the first processing result corresponding to the first subtask meets the end trigger condition corresponding to the first subtask, then the second subtask continues to be analyzed and processed through the warehouse planning model.

[0016] In some embodiments, the method also includes: if the confirmation information input by the user on the user interaction interface for the first processing result does not meet the end trigger condition corresponding to the first subtask, then it is determined that there is an abnormality in the first processing result; or, if the number of abnormal information input by the user on the user interaction interface for the first processing result exceeds a preset number threshold, then it is determined that there is an abnormality in the first processing result.

[0017] In some embodiments, at least one subtask includes a first subtask, and the warehouse planning model includes a task execution submodel and a result verification submodel. The method also includes: based on at least one feedback information corresponding to the first subtask, verifying the first processing result corresponding to the first subtask through the result verification submodel to obtain a verification result; if the verification result is abnormal, re-analyzing and processing the first subtask through the task execution submodel, and re-determining the processing result corresponding to the first subtask.

[0018] In some embodiments, the user interaction interface includes a progress bar; the method also includes: determining the progress information of each subtask in response to at least one feedback information input by the user for at least one request information corresponding to each subtask; and displaying the task completion degree of the task to be processed through a progress bar based on the progress information of each subtask.

[0019] In some embodiments, the user interaction interface includes an assistant window, and the method also includes: obtaining at least one question and answer information regarding the planning results input by the user in the assistant window; processing at least one question and answer information through a warehouse planning model, and controlling the assistant window to display result information corresponding to the question and answer information.

[0020] The second aspect of the embodiment of the present application provides a warehouse planning device, which includes an acquisition module, a splitting module, a processing module, a determination module and a control module. Among them, the acquisition module is configured to acquire the pending tasks input by the user in the user interaction interface. The splitting module is configured to split and process the pending tasks through the warehouse planning model to obtain at least one subtask. The processing module is configured to analyze and process each subtask through the warehouse planning model to obtain at least one request information corresponding to each subtask. The determination module is configured to determine the processing results corresponding to each subtask through the warehouse planning model in response to at least one feedback information input by the user for at least one request information corresponding to each subtask; based on the processing results corresponding to each subtask in at least one subtask, determine the planning results corresponding to the pending tasks through the warehouse planning model. The control module is configured to control the user interaction interface to display each of the request information, and control the user interaction interface to display the planning results.

[0021] A third aspect of an embodiment of the present application provides an electronic device, comprising: a processor and a memory, the memory being used to store computer executable instructions; the processor being used to read the instructions from the memory and execute the instructions to implement the warehouse planning method described in the first aspect above.

[0022] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the storage medium stores computer program instructions. When a computer reads the instructions, the warehouse planning method described in the first aspect is executed.

[0023] A fifth aspect of an embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the warehouse planning method described in the first aspect above.

[0024] A sixth aspect of an embodiment of the present application provides a computer program, which, when executed by a processor, can implement the warehouse planning method described in the first aspect above.

[0025] The warehouse planning method provided in the embodiment of the present application uses a trained warehouse planning model to split the acquired pending tasks into at least one subtask, and then analyzes and processes each subtask to obtain at least one request information corresponding to each subtask, and the request information can be used to prompt the user to input relevant project information of the warehouse system required to execute the pending tasks; after the user inputs the corresponding feedback information according to the request information, the warehouse planning model can determine the processing results of each subtask according to the acquired feedback information, and determine the planning results corresponding to the pending tasks according to the processing results of each subtask, and display the final planning results on the user interaction interface, thereby completing the planning of the warehouse system. The warehouse planning method provided in the present application can realize that before deploying the warehouse system, the warehouse planning model can collect the project information required for warehouse system planning through multiple interactions with users, and provide users with instant warehouse planning solutions, and can also answer questions related to the warehouse system for users, improve the planning efficiency of the warehouse system, reduce the manpower cost of planning, and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1A schematic diagram of a warehouse planning system provided in an embodiment of the present application;

[0028] Figure 2 A schematic diagram of a storage system planning method provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of another storage system planning method provided in an embodiment of the present application;

[0030] Figure 4 A schematic diagram of another storage system planning method provided in an embodiment of the present application;

[0031] Figure 5 A schematic diagram of another storage system planning method provided in an embodiment of the present application;

[0032] Figure 6 A schematic diagram of a user interaction interface provided in an embodiment of the present application;

[0033] Figure 7 A schematic diagram of another user interaction interface provided in an embodiment of the present application;

[0034] Figure 8 A schematic diagram of another user interaction interface provided in an embodiment of the present application;

[0035] Fig. 9 A schematic diagram of a storage planning device provided in an embodiment of the present application;

[0036] Fig.10 A schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention and to make the above-mentioned purposes, features and advantages of the embodiments of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention are further described in detail below with reference to the accompanying drawings.

[0038] Before deploying a warehousing system, users may want to know the deployment plan of the warehousing system in advance to determine whether the deployment plan meets their needs. Therefore, the planners of the warehousing system need to understand the project parameters and requirements of the user's warehousing system, and start deploying the warehousing system after collecting relevant information.

[0039] For example, planners may need to go to the user site to collect project information and understand user needs in order to deploy the warehousing system solution, which results in the information collection process and solution deployment process taking a long time and high labor costs. When users are not satisfied with the deployed solution, planners also need to make continuous adjustments and redeploy according to user needs, which reduces the planning efficiency of the warehousing system, further increases labor costs, and also reduces user experience.

[0040] In order to solve the above problems, the embodiments of the present application provide a warehouse planning method and a warehouse planning device. By constructing a warehouse system planning system, the system can integrate the planning solution knowledge base of various industries in warehousing and logistics, provide instant solution design and answers through natural language interaction, and quickly generate simulation results, thereby improving pre-sales planning efficiency, reducing dependence on human resources, and promoting the unmanned front-end process.

[0041] In some examples, the warehouse planning method provided in the embodiments of the present application can be implemented through a warehouse planning system.

[0042] Figure 1 A schematic diagram of a warehouse planning system provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the warehouse planning system 1 includes a front end 10 and a back end 20. The front end 10 may be a display end for displaying a user interaction interface. The back end 20 may be a server end for implementing the planning of the warehouse system and controlling the front end 10 to display the planning results.

[0043] In some examples, the front end 10 and the back end 20 may be deployed on the same device or on different devices, which is not limited in the embodiments of the present application.

[0044] For example, the front end 10 and the back end 20 may both be deployed on a server or a terminal device; or, the front end 10 may be deployed on a terminal device, and the back end 20 may be deployed on a server. The terminal device may include at least one of a personal computer, a laptop, a smart phone, a tablet computer, and a portable wearable device; the server may include an independent server or a server cluster composed of multiple servers, which is not limited in the present embodiment.

[0045] Figure 2 A schematic diagram of a warehouse planning method provided in an embodiment of the present application is shown as follows: Figure 2 As shown, the method includes steps 110 to 140 as shown below.

[0046] Step 110: Obtain the to-be-processed tasks input by the user in the user interaction interface.

[0047] In some examples, the front end 10 of the warehouse planning system 1 may display a user interaction interface, which may receive information input by the user and display information output by the back end, thereby realizing interaction between the user and the warehouse planning system 1. For example, the user interaction interface may be a GPT (Generative Pre-trained Transformer) interaction interface, which may include an interaction window, which may display information output by the back end 20 and information input by the user.

[0048] For example, Figure 1 As shown, the backend 20 of the warehouse planning system 1 may be deployed with a warehouse planning model 200. The warehouse planning model 200 may be pre-trained and stored in the backend 20, and the warehouse planning model 200 may include multiple sub-models. For example, the warehouse planning model 200 includes a task splitting sub-model 210 and a task execution sub-model 220.

[0049] In some examples, after the user inputs information through the user interaction interface, the input module 111 of the front end 10 can send the input information to the back end 20, and the back end 20 determines the input information as a task to be processed, or the back end 20 processes the input information and determines the task to be processed.

[0050] That is, the task to be processed may be user input information or processed input information. For example, the backend 20 may pre-process the user input information, such as performing data identification, data cleaning, data conversion, and data correction on the user input information in sequence, and then determine the task to be processed. For example, the task to be processed determined by the backend 20 may be "planning a warehousing plan."

[0051] Step 120: split the task to be processed by using the warehouse planning model to obtain at least one subtask.

[0052] For example, after determining the pending tasks, the pending tasks can be split through the warehouse planning model, and the pending tasks can be split into at least one subtask to further analyze and process each subtask.

[0053] In some embodiments, Figure 1 As shown, after the tasks to be processed are obtained, the tasks to be processed can be split by the task splitting submodel 210 in the warehouse planning model 200.

[0054] Exemplarily, after obtaining the task to be processed, the task splitting sub-model 210 can first determine whether the task to be processed needs to be split. If the task to be processed does not need to be split, the task to be processed is sent to the task execution sub-model 220 for further processing; if the task to be processed needs to be split, after the task to be processed is split, the multiple sub-tasks after splitting are sent to the task execution sub-model 220 for further processing.

[0055] That is to say, the number of at least one subtask corresponding to the pending task can be one or more. When the number of at least one subtask is one, the subtask is a pending task. The embodiment of the present application takes the number of at least one subtask as more than one, that is, the task splitting submodel 210 splits the pending task to obtain multiple subtasks as an example for illustrative description.

[0056] In some embodiments, the above step 120 includes: based on the complexity of the task to be processed and a preset splitting principle, splitting the task to be processed into at least one subtask through a task splitting sub-model.

[0057] Exemplarily, the preset splitting principle includes that the number of tasks of at least one subtask is less than or equal to a preset number threshold and / or the correlation between any two subtasks in at least one subtask is less than or equal to a preset correlation threshold.

[0058] In some examples, if the task to be processed is relatively complex (i.e., the complexity of the task to be processed is relatively high), it is necessary to split the task to be processed; if the task to be processed is relatively simple (i.e., the complexity of the task to be processed is relatively low), it is not necessary to split the task to be processed. Among them, the complexity of the task to be processed can be used to indicate the complexity of completing the task to be processed. For example, the complexity of the task to be processed can be related to the amount and difficulty of parameter information required to be collected to perform the task to be processed. When the parameter information required to be collected to perform the task to be processed is large and complex, it can be determined that the complexity of the task to be processed is large; when the parameter information required to be collected for the task to be processed is small and simple, it can be determined that the complexity of the task to be processed is small.

[0059] In some examples, a preset complexity threshold may be set. After obtaining the task to be processed, the task splitting sub-model 210 may score the complexity of the task to be processed according to the amount and difficulty of parameter information required to collect for executing the task to be processed. When the complexity of the task to be processed is greater than the preset complexity threshold, the task to be processed may be split into multiple sub-tasks by the task splitting sub-model 210, and the complexity of each sub-task obtained after the splitting is less than or equal to the preset complexity threshold. When the complexity of the task to be processed is less than or equal to the preset complexity threshold, there is no need to perform splitting processing on the task to be processed.

[0060] For example, when the pending task is "design a warehousing plan", since the execution of this task requires the collection of a large amount of parameter information of the warehousing system, the pending task can be split. When the pending task is "what are the storage methods of the warehousing system", the pending task is relatively simple and may not require the collection of parameter information of the warehousing system. Therefore, there is no need to split the pending task.

[0061] For example, when it is determined that the task to be processed needs to be split according to the complexity of the task to be processed, the task to be processed can be further split according to a preset splitting principle. The preset splitting principle may include that the number of subtasks after splitting does not exceed a preset number threshold, and / or that similar or identical tasks are divided into the same subtask as much as possible.

[0062] That is, the number of subtasks after splitting cannot be too large, and / or the correlation between any two subtasks is small, such as smaller than a preset correlation threshold.

[0063] In some examples, the complexity of any subtask after splitting is relatively small, such as less than or equal to a preset complexity threshold.

[0064] Exemplarily, a preset task splitting library may be pre-set in the warehouse planning system 1, and the preset task splitting library stores the correspondence between multiple tasks to be split and the subtasks after splitting corresponding to each task to be split. After receiving the task to be processed, it can be determined whether there is a task to be processed in the preset task splitting library based on the task to be processed and the preset task splitting library. If there is a task to be processed in the preset task splitting library, at least one subtask matching the task to be processed is determined.

[0065] That is to say, the present application can also store the splitting situations corresponding to the planning results that satisfy the user based on the historical splitting experience, so that the corresponding subtasks can be directly obtained when the same or similar tasks to be processed are encountered in the future.

[0066] For example, the task to be processed can be split into two subtasks, namely the first subtask and the second subtask. It should be noted that the present embodiment of the application takes the splitting of the task to be processed into two subtasks as an example for illustrative description, and the task to be processed can also be split into a larger number of subtasks, which is not limited in the present embodiment of the application.

[0067] The warehouse planning method provided in the embodiment of the present application realizes the splitting and processing of tasks to be processed through the task splitting sub-model in the warehouse planning model, splitting more complex tasks to be processed into multiple simple and easy-to-process sub-tasks, thereby facilitating further processing of subsequent task execution sub-models.

[0068] Step 130, analyze and process each subtask through the warehouse planning model to obtain at least one request information corresponding to each subtask, and control the user interaction interface to display each request information; in response to at least one feedback information input by the user for the at least one request information corresponding to each subtask, determine the processing result corresponding to each subtask through the warehouse planning model.

[0069] In some embodiments, Figure 1 As shown, the warehouse planning model 200 includes a task execution sub-model 220. After the task splitting sub-model 210 splits the task to be processed into multiple sub-tasks, the multiple sub-tasks can be sent to the task execution sub-model 220 respectively, and the task execution sub-model 220 analyzes and processes each sub-task.

[0070] In some examples, after receiving multiple subtasks, the task execution sub-model 220 may determine the execution order of each of the multiple subtasks, and analyze and process each of the subtasks in sequence according to the order of each subtask.

[0071] In some examples, there may be mutual influence between the subtasks, that is, the processing result of the previous subtask (such as the first subtask) may affect the processing of the next adjacent subtask (such as the second subtask). For example, after the task execution submodel 220 determines the first processing result corresponding to the first subtask, it can analyze and process the second subtask based on the first subtask to determine the second processing result corresponding to the second subtask.

[0072] Combine the following Figure 3 , taking at least one subtask including a first subtask and a second subtask as an example, the analysis and processing process of each subtask (ie, the first subtask and the second subtask) by the task execution submodel 220 is explained.

[0073] Figure 3 A schematic diagram of another storage planning method provided in an embodiment of the present application. Figure 3 As shown, the above step 130 includes steps 1311 to 1315 as shown below.

[0074] Step 1311: Analyze and process the first subtask based on the task execution submodel, determine the first request information corresponding to the first subtask, and control the user interaction interface to display the first request information.

[0075] In some examples, after receiving the first subtask, the task execution submodel 220 may determine the first request information corresponding to the first subtask, wherein the request information corresponding to each subtask may be the project information or other information of the storage system required to be collected to solve each subtask.

[0076] For example, the request information may be at least one question information, and the project information of the storage system can be collected by the user answering the question information; or the request information may also be at least one reply information, and the reply information may be reply information to the question raised by the user. The specific form of the request information is not limited in the embodiments of the present application.

[0077] In some examples, each subtask may correspond to one request information or multiple request information. The number of request information corresponding to each subtask may be the same or different.

[0078] Exemplarily, after determining the request information corresponding to each subtask (such as the first subtask), the backend 20 can control the output module 112 of the frontend 10 to display each request information (such as the first request information) on the user interaction interface. For example, the first request information corresponding to the first subtask can be "How many meters are the length, width and height of your warehouse?".

[0079] Step 1312, in response to the first feedback information input by the user for the first request information corresponding to the first subtask, determine the second request information corresponding to the first subtask through the task execution submodel, and control the user interaction interface to display the second request information.

[0080] In some examples, after the user interaction interface displays the first request information, the user may input first feedback information in the user interaction interface to reply to the first request information.

[0081] For example, when the first request information is question information, the feedback information may be the user's reply information to the question information. When the first request information is reply information, the first feedback information may be question information or other question information to the reply information; or the feedback information may be other information. In other words, the feedback information may be different depending on the request information.

[0082] For example, when the first request information is "How long, wide and high are your warehouse? What storage method do you need? What type of business do you need?", the first feedback information can be the answer information "The length, width and height of the warehouse are 50, 60 and 4 respectively", or it can be the question information "What is the storage method".

[0083] Exemplarily, after obtaining the first feedback information, the task execution sub-model 220 can determine the second request information corresponding to the first sub-task according to the first feedback information. In other words, the second request information is determined based on the first feedback information, that is, the subsequent request information (i.e., the second request information) of the same sub-task is affected by the feedback information (i.e., the first feedback information) of the previous request information (i.e., the first request information).

[0084] In some examples, the second request information may be question information different from the first request information, or may be answer information to the first feedback information, which is not limited in this embodiment of the present application.

[0085] For example, when the first feedback information is "The length, width and height of the warehouse are 50, 60 and 4 respectively", the second request information may be "The units of the warehouse length, width and height you provided are not clear. Is the unit in meters?"; or, when the first feedback information is "What is the storage method", the second request information may be "The storage method refers to the storage unit in logistics warehousing, mainly including..." and other reply information to the storage method; or, the second request information may also be "Do you need to provide the type of business you need?" and other information.

[0086] That is, after obtaining the first feedback information input by the user for the first request information, the second request information can be generated according to the first feedback information, and the user interaction interface can be controlled to display the second request information.

[0087] Step 1313: In response to the second feedback information input by the user in response to the second request information, based on the first feedback information and the second feedback information, determine a first processing result corresponding to the first subtask through the task execution sub-model.

[0088] In some examples, after the backend 20 controls the user interaction interface to display the second request information, the user may continue to input second feedback information for the second request information through the user interaction interface.

[0089] For example, when the second request information may be "The units of the warehouse length, width and height you provided are not clear. Is the unit in meter?", the second feedback information may be "Yes"; when the second request information may be "The storage method refers to the storage unit in logistics warehousing, mainly including...", the second feedback information may be "Storage on shelves"; when the second request information may be "Do you need to provide the type of business you need? B2B, B2C or B2B&B2C", the second feedback information may be "B2B".

[0090] Exemplarily, after the information collection of the first subtask is completed, there is no need to generate request information. The collected information of the first subtask includes the first feedback information and the second feedback information. Based on the first feedback information and the second feedback information, the first processing result corresponding to the first subtask is determined by the task execution submodel 220. In other words, the processing result of each subtask can be determined according to all the feedback information corresponding to each subtask.

[0091] In some examples, after the first processing result of the first subtask is obtained, the user interaction interface may be controlled to display the first processing result.

[0092] In some examples, the first processing result corresponding to the first subtask may be summary information of the collected information (including the first feedback information and the second feedback information), so that the summary information is displayed to the user for confirmation through the user interaction interface; or, the first processing result of the first subtask may also be displayed through the user interaction interface in a combination of text and graphics. For example, the first processing result may be related to the task objective of the first subtask. For example, when the task objective of the first subtask is to determine the efficiency index of the warehousing system, the first processing result of the first subtask may be information generated based on the first feedback information and the second feedback information to display the efficiency index of the warehousing system.

[0093] It should be noted that the process of determining the first processing result corresponding to the first subtask through the task execution sub-model 220 is described in detail in the following embodiments (such as steps 1321 to 1323).

[0094] In some examples, some of the multiple subtasks may not need to determine the corresponding processing results, which is not limited in the present embodiment. For example, the processing result corresponding to the subtask may also be the feedback information collected last time, or the processing result may also be all feedback information.

[0095] Step 1314, based on at least one feedback information corresponding to the first subtask, analyze and process the second subtask through the warehouse planning model, determine at least one request information corresponding to the second subtask, and control the user interaction interface to display the at least one request information corresponding to the second subtask.

[0096] The second subtask is the next subtask of the first subtask.

[0097] In some examples, after obtaining the first processing result corresponding to the first subtask, the second subtask can be analyzed and processed based on at least one feedback information corresponding to the first subtask through the task execution submodel 220 to determine at least one request information corresponding to the second subtask. In other words, the task execution submodel 220 can determine the information collection of the second subtask based on the information collection of the first subtask.

[0098] In some embodiments, the above step 1314 includes: analyzing and processing the second subtask through the task execution sub-model to obtain at least one request information corresponding to the second subtask; if there is feedback information corresponding to the third request information in at least one feedback information corresponding to the first subtask, and there is no feedback information corresponding to the fourth request information in at least one feedback information corresponding to the first subtask, then controlling the user interaction interface not to display the third request information and to display the fourth request information; if there is no feedback information corresponding to the third request information in at least one feedback information corresponding to the first subtask, then controlling the user interaction interface to display the third request information.

[0099] Exemplarily, the at least one request information corresponding to the second subtask may include third request information. After determining the third request information, the task execution submodel 220 may compare the third request information with the first request information and the second request information corresponding to the first subtask.

[0100] In some examples, if the third request information is the same as the first request information or the second request information, it indicates that the feedback information corresponding to the third request information is also the same as the first feedback information or the second feedback information. In this case, the first feedback information and the second feedback information corresponding to the first subtask include the feedback information corresponding to the third request information. In other words, the feedback information required for the third request information has been collected during the processing of the first subtask, so there is no need to collect it repeatedly. Therefore, there is no need to control the user interaction interface to display the third request.

[0101] It should be noted that the multiple request information involved in the present application is not necessarily the same as the multiple request information, but the multiple request information may also express the same meaning or the same requirements.

[0102] For example, when there is feedback information corresponding to the third request information in at least one feedback information corresponding to the first subtask, the fourth request information corresponding to the second subtask is further determined, and the fourth request is compared with at least one request information corresponding to the first subtask. The processing process of the fourth request information is similar to that of the third request, and will not be repeated here to avoid repetition.

[0103] In other examples, if the third request information is different from the first request information and the second request information, it indicates that the feedback information corresponding to the third request information may also be different from the first feedback information and the second feedback information. In this case, the first feedback information and the second feedback information corresponding to the first subtask may not include the feedback information corresponding to the third request information. Therefore, it is necessary to control the user interaction interface to display the third request to obtain the third feedback information corresponding to the third request information.

[0104] In the warehouse planning method provided in the embodiment of the present application, when the information involved in the subsequent subtask (such as the second subtask) to be executed has been collected during the execution of the previous subtask (such as the first subtask), there is no need to collect it again and it can be used directly, thereby further improving the efficiency of warehouse planning.

[0105] Step 1315 , in response to at least one feedback information input by the user for at least one request information corresponding to the second subtask, determining a second processing result corresponding to the second subtask through the warehouse planning model.

[0106] For example, when it is determined that there is no feedback information corresponding to the fourth request information in the at least one feedback information corresponding to the first subtask, the user interaction interface is controlled to display the fourth request information, and feedback information (such as the fourth feedback information) input by the user for the fourth request information is received.

[0107] In some examples, after determining at least one piece of feedback information (such as all feedback information) corresponding to the second subtask, a second processing result corresponding to the second subtask is determined based on the at least one piece of feedback information. The at least one piece of feedback information corresponding to the second subtask includes feedback information corresponding to the third request information (such as obtained from at least one piece of feedback information corresponding to the first subtask) and feedback information corresponding to the fourth request information.

[0108] Step 140, based on the processing results corresponding to each subtask in at least one subtask, determine the planning results corresponding to the task to be processed through the warehouse planning model, and control the user interaction interface to display the planning results.

[0109] In some embodiments, based on the first processing result of the first subtask and the second processing result of the second subtask, the planning result corresponding to the task to be processed is determined through the task execution submodel in the warehouse planning model, and the user interaction interface is controlled to display the planning result.

[0110] In some examples, the planning result corresponding to the pending task may be the deployment and planning of the storage system corresponding to the pending task. For example, the planning result may be displayed in the form of simulation data, pictures, text, etc., which is not limited in the embodiments of the present application. The user can understand the specific deployment of the storage system in advance through the display of the planning results. When the user is not satisfied with the current deployment, the user can also adjust the project parameters to obtain new planning results.

[0111] The warehouse planning method provided in the embodiment of the present application uses a trained warehouse planning model to split the acquired pending tasks into at least one subtask, and then analyzes and processes each subtask to obtain at least one request information corresponding to each subtask, and the request information can be used to prompt the user to input relevant project information of the warehouse system required to execute the pending tasks; after the user inputs the corresponding feedback information according to the request information, the warehouse planning model can determine the processing results of each subtask according to the acquired feedback information, and determine the planning results corresponding to the pending tasks according to the processing results of each subtask, and display the final planning results on the user interaction interface, thereby completing the planning of the warehouse system. The warehouse planning method provided in the present application can realize that before deploying the warehouse system, the warehouse planning model can collect the project information required for warehouse system planning through multiple interactions with users, and provide users with instant warehouse planning solutions, and can also answer questions related to the warehouse system for users, improve the planning efficiency of the warehouse system, reduce the manpower cost of planning, and improve user experience.

[0112] The following is combined with Figure 4 The process of determining the processing result corresponding to the subtask (such as the first subtask or the second subtask) through the task execution submodel is described.

[0113] Figure 4 A schematic diagram of another storage planning method provided in an embodiment of the present application. Figure 4 As shown, the above step 130 includes the following steps 1321 to 1323. It should be noted that the above steps 1313 and 1315 can be implemented through the following steps 1321 to 1323.

[0114] Step 1321, determine the task objectives and preset algorithm library of the subtask.

[0115] In some examples, after acquiring each subtask, the task execution submodel 220 may determine the task objectives of each subtask. For example, when at least one subtask includes a first subtask and a second subtask, the task objective of the first subtask may be to determine the efficiency index of the warehousing system, and the task objective of the second subtask may be to provide a planning scheme for the warehousing system. The result obtained by achieving the task objective of the subtask is the processing result corresponding to the subtask.

[0116] It should be noted that when the task to be processed is divided into multiple subtasks, the task objective of the last subtask to be executed may be to determine the planning scheme of the warehousing system, and the processing result of the last subtask is the planning result of the warehousing system.

[0117] In some examples, the backend of the warehouse planning system may store a preset algorithm library, which may include multiple algorithms. The algorithm may be a function or a pre-trained neural network model. For example, the function may be a network search function, a code execution function, and a subtask submission function, etc., which is not limited in the embodiments of the present application.

[0118] Step 1322: Based on the task objective of the subtask, the preset algorithm library, and at least one piece of feedback information corresponding to the subtask, determine the task execution information corresponding to the subtask through the first execution network.

[0119] In some examples, after determining the task objective of the first subtask, a preset algorithm library may be obtained, and the task objective of the first subtask, the preset algorithm library, and at least one feedback information of the first subtask (such as the first feedback information and the second information) may be sent to the task execution submodel 220. The at least one feedback information of the first subtask may also be referred to as the collected information corresponding to the first subtask.

[0120] In some embodiments, Figure 1 As shown, the task execution sub-model 220 includes a first execution network 221 and a second execution network 222. The first execution network 221 is used to determine the task execution information corresponding to the sub-task according to the task target of the sub-task, the preset algorithm library, and at least one feedback information corresponding to the sub-task, and send the task execution information to the second execution network 222. The second execution network 222 executes the sub-task according to the task execution information determined by the first execution network 221, and determines the processing result of the sub-task.

[0121] Exemplarily, the task execution information is used to indicate a target execution method for achieving the task goal of the subtask. In other words, the task execution information is used to indicate that the task goal of the subtask is achieved through a target execution method. Among them, the target execution method includes calling at least one algorithm in a preset algorithm library. For example, among multiple subtasks, some subtasks can be achieved by calling one algorithm, and some subtasks may need to call multiple algorithms to be achieved. The algorithms called when achieving the task goals of each subtask can be the same or different, and the embodiments of the present application do not limit this.

[0122] It should be noted that the task goal of implementing the above subtasks is to determine the processing results of the subtasks.

[0123] In some examples, the first execution network 221 can determine that the task goal of the first subtask can be achieved by calling the target algorithm in the preset algorithm library, so as to obtain the first processing result, based on the task goal of the first subtask, the preset algorithm library, and at least one feedback information corresponding to the first subtask. In other words, the first execution network 221 can generate task execution information for calling the target algorithm to achieve the task goal, and send the task execution information to the second execution network 222.

[0124] For example, the preset algorithm library includes Algorithm 1 and Algorithm 2, wherein Algorithm 1 is a network search function, and Algorithm 2 is a trained efficiency prediction model. The task execution information generated by the first execution network 221 may include: calling Algorithm 1 to determine "what is the storage method", or the task execution information generated by the first execution network 221 may also include: calling Algorithm 2 to determine the efficiency index of the warehousing system.

[0125] Step 1323: Based on the task execution information, determine the processing result corresponding to the subtask through the second execution network.

[0126] In some embodiments, step 1323 includes: based on the task execution information and at least one feedback information corresponding to the subtask, generating a processing result corresponding to the subtask by calling the efficiency prediction model through the second execution network.

[0127] For example, after receiving the execution information of the first subtask, the second execution network 222 can call at least one algorithm in the preset algorithm library to achieve the task goal of the first subtask based on the task execution information and at least one feedback information corresponding to the first subtask, and obtain the first processing result corresponding to the first subtask.

[0128] In some embodiments, the task objective of the subtask includes determining the efficiency index of the warehousing system, and the target execution method includes calling the efficiency prediction model in the preset algorithm library. The processing result includes multiple sets of prediction information, and the multiple sets of prediction information are used to indicate the efficiency indexes corresponding to the multiple sets of system parameters in the warehousing system.

[0129] For example, the efficiency prediction model may be pre-trained and stored, and the efficiency prediction model may be dynamically updated. For example, the efficiency prediction model may be updated according to the processing results of the subtask. Multiple groups of efficiency indicators of the warehousing system may be obtained through the efficiency prediction model, and the user may select the most satisfactory efficiency indicator according to the multiple groups of efficiency indicators, thereby further determining the corresponding warehousing planning scheme.

[0130] The planning method of the warehousing system provided in the embodiment of the present application further determines the processing result corresponding to each subtask by setting a preset algorithm library and collecting feedback information of each subtask and the preset algorithm library. Different algorithms are used for different subtasks to improve execution efficiency.

[0131] In some examples, the task objective of the subtask may be to determine an efficiency index of a warehousing system. The following further illustrates step 1323 by taking the task objective of the subtask being to determine an efficiency index of a warehousing system as an example.

[0132] Figure 5 Another storage planning method provided in the embodiment of the present application is as follows: Figure 5 As shown, the above step 1323 includes steps 13231 to 13234 as shown below.

[0133] Step 13231, determining target input information based on at least one feedback information corresponding to the subtask.

[0134] Among them, the target input information includes warehouse size, handling equipment type and vehicle handling efficiency. The vehicle handling efficiency includes the number of vehicle handling times and the vehicle dwelling time.

[0135] In some examples, after obtaining the task execution information and at least one feedback information, the second execution network 222 can determine the target input information of the efficiency prediction model based on the at least one feedback information. The at least one feedback information can be all feedback information corresponding to the subtask (i.e., all information collected) or partial feedback information (i.e., partial information collected), which is not limited in the embodiments of the present application.

[0136] For example, the information required to achieve the task goal of the subtask in at least one feedback information can be determined as the information to be processed. The information to be processed may include the warehouse size corresponding to the warehousing system, such as the length, width and height of the warehouse, and may also include the user's requirements for the picking efficiency and picking time of the warehousing system, as well as the size of the carrier in the warehousing system and the load of the handling equipment (such as the maximum load of the handling equipment), etc.; at the same time, the information to be processed may also include the business type required by the user, wherein the business type includes B2B (Business-to-Business) and B2C (Business-to-Consumer).

[0137] In some examples, after determining the information to be processed, the target input information can be further determined based on the information to be processed. The target input information includes warehouse size, handling equipment type, and carrier handling efficiency. Among them, the handling equipment can be a handling robot, such as an automated guided vehicle (AGV), and the handling equipment includes a carrier handling equipment that can be used to transport a carrier, and can also include a container handling equipment for transporting to a container, which is not limited in the embodiments of the present application.

[0138] For example, the type of handling equipment in the target input information can be determined based on the warehouse size, carrier size, and maximum load of the handling equipment in the information to be processed. Since different types of handling equipment have different sizes, heights, and load-bearing capacity, the type of handling equipment suitable for the user's storage system is determined based on the user's warehouse size, carrier size, and the maximum load of the required handling equipment. It should be noted that a storage system may include at least one (such as one or more) types of handling equipment, and this embodiment of the application is not limited to this.

[0139] For another example, the vehicle transport efficiency in the target input information, such as the number of vehicle transports and the vehicle dwell time, may be determined according to the business type in the information to be processed.

[0140] For example, when users have different requirements for picking efficiency, the corresponding carrier handling efficiency is also different. For example, when users have higher requirements for picking efficiency, the determined carrier handling efficiency will be higher. Therefore, the carrier handling efficiency suitable for the warehousing system can be determined based on the user's requirements for picking efficiency. At the same time, different business types correspond to different order volumes, delivery requirements, and timeliness requirements. Therefore, this application can also determine the optimal carrier handling efficiency corresponding to the warehousing system based on the specific business type.

[0141] In some examples, a preset algorithm (such as a warehouse experience calculation algorithm) may also be pre-set in the warehouse planning system. The preset algorithm may perform convergence processing on the initial parameter information or the information to be processed, so as to determine the target input information corresponding to the target efficiency prediction model.

[0142] For example, the preset algorithm may include matching relationships between multiple sets of data to be processed and multiple sets of input data. After determining the information to be processed, it can be determined whether the information to be processed exists in the multiple data to be processed with matching relationships. If so, the input data matching the information to be processed is determined as the target input information.

[0143] It should be noted that multiple groups of data to be processed and multiple groups of input data can be obtained based on historical data, and the embodiment of the present application does not limit the specific form of the preset algorithm.

[0144] Step 13232: Process the target input information based on the first prediction sub-model to obtain the target configuration parameters of the warehousing system.

[0145] In some embodiments, the efficiency prediction model includes a first prediction sub-model and a second prediction sub-model, wherein the first prediction sub-model and the second prediction sub-model are pre-trained and stored.

[0146] Exemplarily, the target configuration parameters include a first number of each type of handling equipment and / or a second number of workstations.

[0147] In some examples, the target input information is input into the first prediction sub-model, and after being processed by the first prediction sub-model, the first quantity of each type of handling equipment corresponding to the warehousing system, or the second quantity of workstations corresponding to the warehousing system, or the first quantity of each type of handling equipment and the second quantity of workstations corresponding to the warehousing system can be output.

[0148] It should be noted that, if there are multiple types of transport equipment in the target input information, the quantity of each type of transport equipment, that is, multiple first quantities, can be determined respectively through the first prediction sub-model.

[0149] In some embodiments, before executing step 13232, the method also includes: determining the warehouse type corresponding to the warehousing system based on the warehouse size; determining the target efficiency prediction model corresponding to the target input information based on the warehouse type; wherein different warehouse types correspond to different target efficiency prediction models.

[0150] In some examples, a warehouse planning system (such as a backend of a warehouse planning system) may store a plurality of different efficiency prediction models and may determine an efficiency prediction model corresponding to target input information based on the warehouse type.

[0151] Exemplarily, the first prediction sub-models in different efficiency prediction models may be different. That is, the first prediction sub-model corresponding to the target input information may be determined based on the warehouse type.

[0152] In some examples, multiple warehouse types may be set, and there is a matching relationship between each warehouse type and each first prediction sub-model. For example, a corresponding warehouse size range may be configured for each warehouse type, and the warehouse type of the warehousing system may be determined based on the warehouse size range in which the warehouse size is located. Then, the first prediction sub-model corresponding to the target input information is determined based on the matching relationship between the first prediction sub-model and the warehouse type.

[0153] For example, warehouses can be divided into three types of warehouses, namely large warehouses, medium warehouses and small warehouses, according to their sizes. When the warehouse types are divided into three types, three first prediction sub-models can be pre-set, namely the first prediction sub-model A, the first prediction sub-model B and the first prediction sub-model C. Among them, the three first prediction sub-models correspond to the three warehouse types one by one. For example, when the warehouse size is large and belongs to a large warehouse, it can be determined that the target input information corresponds to the first prediction sub-model A. When the warehouse size is regular and belongs to a medium-sized warehouse, it can be determined that the target input information corresponds to the first prediction sub-model B. When the warehouse size is small and belongs to a small warehouse, it can be determined that the target input information corresponds to the first prediction sub-model C.

[0154] It should be noted that the number of the first prediction sub-models may be more or less, and the embodiment of the present application does not limit this. For example, the number of the first prediction sub-models may be related to the number of warehouse types.

[0155] Step 13233, similarity processing is performed on the target configuration parameters using a preset similarity algorithm, and multiple groups of system configuration parameters are expanded.

[0156] In some embodiments, the multiple sets of system configuration parameters include target configuration parameters, and the number of each type of handling equipment in each set of system configuration parameters other than the target configuration parameters in the multiple sets of system configuration parameters is different from the corresponding first number, and / or the number of workstations is different from the second number.

[0157] In some examples, the preset similarity algorithm can determine multiple groups of different system configuration parameters based on the first number and the second number in the target configuration parameter. The number of each type of handling equipment and / or the number of workstations in different system configuration parameters are different. In other words, the number of each type of handling equipment in different system configuration parameters is different, or the number of workstations in different system configuration parameters is different, or the number of each type of handling equipment and the number of workstations in different system configuration parameters are both different.

[0158] For example, when the types of handling equipment include two categories, namely, the first handling equipment and the second handling equipment, taking the number of the first handling equipment in the target configuration parameters as 50, the number of the second handling equipment as 100, and the number of workstations as 10 as an example, after similarity processing of the target configuration parameters by the preset similarity algorithm, three groups of system configuration parameters can be obtained. Among them, in the first group of system configuration parameters, the number of the first handling equipment is 45, the number of the second handling equipment is 90, and the number of workstations is 9; the second group of system configuration parameters is the target configuration parameters, that is, the number of the first handling equipment is 50, the number of the second handling equipment is 100, and the number of workstations is 10; in the third group of system configuration parameters, the number of the first handling equipment is 55, the number of the second handling equipment is 110, and the number of workstations is 11.

[0159] Step 13234: Process multiple groups of system configuration parameters based on the second prediction sub-model to determine the efficiency index corresponding to each group of system configuration parameters.

[0160] The efficiency index includes at least one of the workstation utilization rate, handling equipment utilization rate, task cycle time, and number of carriers of the warehousing system.

[0161] In some examples, after determining multiple sets of system configuration parameters, each set of system configuration parameters can be input into the second prediction sub-model in turn, and after being processed by the second prediction sub-model, the efficiency index corresponding to each set of system parameters is obtained. The second prediction sub-model is pre-trained and stored.

[0162] Figure 6 A schematic diagram of a user interaction interface provided in an embodiment of the present application, such as Figure 6 As shown, the user interaction interface 600 displays the processing results of the subtasks (ie, the efficiency index of the warehousing system).

[0163] like Figure 6 As shown in the figure, the processing results of the subtasks displayed on the user interaction interface (i.e., the efficiency index of the warehousing system) can be displayed in the form of a chart. The chart above the user interaction interface shows the efficiency indexes corresponding to the four groups of system configuration parameters, including the utilization rate of handling equipment, the utilization rate of workstations, and the picking efficiency. Among them, the number of handling equipment in each group of system configuration parameters is different, the number of workstations is the same, and the efficiency indexes corresponding to each group of system configuration parameters are different. Users can select the system configuration parameters corresponding to the most appropriate efficiency index according to their needs. Later, the warehousing plan can be planned according to the system configuration parameters.

[0164] like Figure 6 As shown in , the processing results of the subtask also include warehouse deployment diagrams based on different system configuration parameters. Figure 6 A deployment diagram of the warehousing system is shown below the user interaction interface.

[0165] The warehousing planning method provided in the embodiment of the present application can predict the efficiency index of the warehousing system through at least one feedback information corresponding to the subtask (i.e., the information collected by the subtask) and the pre-trained efficiency prediction model. Among them, the efficiency prediction model can obtain the efficiency index corresponding to multiple groups of system configuration parameters, and the user can select the most appropriate efficiency index from the full efficiency index according to actual needs, so as to further determine the final warehousing planning plan.

[0166] In some embodiments, the warehouse planning model also includes a task correction sub-model.

[0167] In some embodiments, after the above step 130, the warehouse planning method also includes: if the first processing result corresponding to the first subtask cannot be determined through the task execution submodel, or if the first processing result corresponding to the first subtask determined by the task execution submodel is abnormal, then the first subtask is optimized through the task correction submodel to obtain an optimized first subtask.

[0168] Exemplarily, the optimization process includes further splitting the first subtask, or adjusting the first subtask to redetermine at least one request information corresponding to the optimized first subtask through the task execution submodel.

[0169] In some examples, the task correction sub-model in the warehouse planning model is used to optimize the sub-tasks (such as the first sub-task) whose processing results cannot be determined by the task execution sub-model, and resend the optimized first sub-task to the task execution sub-model for re-processing by the task execution sub-model. The process of re-analyzing and processing the optimized first sub-task by the task execution sub-model is similar to the process of determining the first sub-task in the above embodiment (such as steps 1311 to 1313), and will not be repeated here to avoid repetition.

[0170] In some embodiments, if the confirmation information entered by the user on the user interaction interface for the first processing result does not meet the end trigger condition corresponding to the first subtask, it is determined that there is an abnormality in the first processing result; or, if the number of abnormal information entered by the user on the user interaction interface for the first processing result exceeds a preset number threshold, it is determined that there is an abnormality in the first processing result.

[0171] In some embodiments, if the confirmation information input by the user on the user interaction interface for the first processing result corresponding to the first subtask meets the end trigger condition corresponding to the first subtask, the second subtask continues to be analyzed and processed through the warehouse planning model.

[0172] In some examples, each subtask (such as the first subtask) corresponds to an end trigger condition, and when the user interaction interface displays the first processing result of the first subtask, the user can enter confirmation information for the first processing result in the user interaction interface. The confirmation information for the first processing result can be used to indicate that the user approves the first processing result, or does not approve the first processing result.

[0173] For example, when the confirmation information input by the user meets the end trigger condition of the first subtask, it indicates that the user approves the first processing result; when the confirmation information input by the user does not meet the end trigger condition of the first subtask, it indicates that the user does not approve the first processing result. When the user does not approve the first processing result, it indicates that there is an abnormality in the first processing result, and the first subtask needs to be optimized through the task correction submodel.

[0174] For example, after the user interaction interface displays the first processing result, the user can be asked whether he is satisfied with the first processing result. If the user enters affirmative expression information such as satisfaction, the end trigger condition corresponding to the first subtask is met, and the task execution submodel continues to execute the second subtask; if the user enters negative expression information such as dissatisfaction, the first subtask is sent to the task correction submodel for optimization processing.

[0175] In other examples, when the user interaction interface displays the first processing result of the first subtask, the user enters exception information for the first processing result in the user interaction interface, and the number of consecutive inputs of the exception information exceeds a preset threshold, it can also be determined that there is an exception in the first processing result.

[0176] For example, when the user interaction interface displays the first processing result and asks the user whether he is satisfied with the first processing result, if the user successively enters three abnormal information unrelated to the first processing result, such as "the weather is very good today", "I have eaten" and "I don't know", then it is considered that there is an abnormality in the first processing result, and the first subtask can be sent to the task correction submodel for optimization processing.

[0177] The warehouse planning method provided in the embodiment of the present application adds a task correction submodel to the warehouse planning model. After determining the processing results of each subtask, it can be determined whether the confirmation information of the processing result by the user meets the end trigger condition of the subtask, and whether the subtask needs to be optimized. When the user is not satisfied with the processing result, the subtask can be optimized in time through the task correction submodel until a processing result satisfactory to the user is obtained, thereby improving the user's satisfaction.

[0178] In some embodiments, the warehouse planning model also includes a result validation sub-model.

[0179] In some embodiments, after the above step 130, the warehouse planning method also includes: based on at least one feedback information corresponding to the first subtask, verifying the first processing result corresponding to the first subtask through a result verification submodel to obtain a verification result; if the verification result is abnormal, re-analyzing and processing the first subtask through the task execution submodel, and re-determining the processing result corresponding to the first subtask.

[0180] In some examples, after determining the first processing result corresponding to the first subtask, the task execution submodel may further verify the first processing result through the result verification submodel to ensure the accuracy of the first processing result.

[0181] For example, when the verification result of the result verification sub-model for the first processing result is normal, the user interaction interface can be controlled to display the first processing result; when the verification result of the result verification sub-model for the first processing result is abnormal, the first subtask is re-analyzed and processed through the task execution sub-model, and the processing result corresponding to the first subtask is re-determined.

[0182] In some examples, the task execution sub-model may send at least one feedback information corresponding to the first sub-task (i.e., the collected information corresponding to the first sub-task) and the first processing result to the result verification sub-model, and the result verification sub-model redetermines the processing result of the first sub-task based on the at least one feedback information. If the redetermined processing result is the same as the first processing result, the verification result is determined to be normal; if the redetermined processing result is different from the first processing result, the verification result is determined to be abnormal.

[0183] The warehouse planning method provided in the embodiment of the present application can perform secondary verification on the processing results corresponding to each subtask by adding a result verification submodel in the warehouse planning model, thereby ensuring the accuracy of the processing results corresponding to each subtask and further improving user satisfaction.

[0184] In some embodiments, the user interaction interface corresponding to the warehouse planning system includes a progress bar.

[0185] Figure 7 A schematic diagram of another user interaction interface provided in an embodiment of the present application. Figure 7 As shown in (a) in FIG. 7 , the user interaction interface 700 a may include multiple windows, such as three windows, and the three windows may be an interaction window 710 , an information input window 720 , and a progress bar window 730 .

[0186] like Figure 7 As shown in (a) of FIG. 7 , the interactive window 710 is used to realize the interaction between the warehouse planning system and the user, that is, the interactive window 710 is used to display the request information corresponding to each subtask, and the feedback information input by the user for the request information. The request information and the feedback information can be displayed in the form of a dialogue. For example, the user can input the task to be processed or the feedback information for the request information through the information input window 720.

[0187] In some examples, the progress bar window 730 includes a progress bar, which is used to display the completion of the task to be processed. The completion of the task to be processed can be determined by the completion of each subtask in the multiple subtasks. The progress bar window 730 can clearly show the user the completion of the processing task, further improving the user experience.

[0188] In some embodiments, the warehouse planning method also includes: determining the progress information of each subtask in response to at least one feedback information input by the user for at least one request information corresponding to each subtask; and displaying the task completion degree of the task to be processed through a progress bar based on the progress information of each subtask.

[0189] In some examples, the task to be processed can be divided into multiple subtasks, and the backend executes each subtask in sequence. When a subtask is completed, the display of the progress bar of the user interaction interface can be controlled. Alternatively, when multiple feedback information needs to be collected during the execution of each subtask, the backend can control the display of the progress bar of the user interaction interface when a feedback information of each subtask is obtained.

[0190] For example, taking the task to be processed as being divided into the first subtask, the second subtask, the third subtask and the fourth subtask, if the backend processes each subtask in sequence, after determining the first processing result corresponding to the first subtask and after the user confirms the first processing result, the display of the progress bar can be adjusted, such as adjusting the display of the progress bar to 25% (such as Figure 7 After the fourth subtask is completed, that is, when the planning result corresponding to the final task to be processed is obtained, the progress bar can be adjusted to 100% (as shown in (a)). Figure 7 , as shown in (b) in the figure).

[0191] For another example, a task to be processed is divided into a first subtask and a second subtask, wherein the first subtask may include a first request information and a second request information, and the second subtask includes a third request information and a fourth request information. When the user inputs the first feedback information for the first request information in the user interaction interface, and the backend generates the second request information, the display of the progress bar can be adjusted, such as adjusting the display of the progress bar to 25%; after obtaining the fourth feedback information corresponding to the second subtask, the display of the progress bar can be adjusted to 100%. It should be noted that when the last feedback information of the last subtask is obtained, it indicates that all information for implementing the task to be processed has been collected. In this case, the display of the progress bar can also be adjusted to 100%.

[0192] The warehouse planning method provided in the embodiment of the present application sets a progress bar on the user interaction interface, which can provide a more intuitive display of the execution status of the tasks to be processed, thereby facilitating the user to more clearly understand the completion degree of the tasks to be processed and improving the user experience.

[0193] In some embodiments, the user interaction interface includes a feedback window.

[0194] In some embodiments, after the above step 140, the warehouse planning method also includes: obtaining at least one question and answer information regarding the planning results input by the user in the interactive window; processing the at least one question and answer information through the warehouse planning model, and controlling the feedback window to display the results corresponding to the question and answer information.

[0195] In some examples, when a planning result of a warehousing system is determined and the planning result is displayed on a user interaction interface, the user interaction interface may include a result display window and a feedback window.

[0196] For example, the result display window can display the planning results, and the feedback window is used to receive the user's question and answer information regarding the feedback results. The question and answer information may include the user's satisfaction information regarding the planning results, and may also include the user's consultation information regarding the planning results. For example, when the user is not satisfied with the planning results, the user may input the corresponding requirements, and the warehouse planning model may redeploy the planning scheme of the warehouse system according to the user's input requirements.

[0197] Figure 8 A schematic diagram of another user interaction interface provided in an embodiment of the present application is shown as follows: Figure 8 As shown, an assistant control can be set on the user interaction interface 800 of the planning results. The user can trigger the assistant control to open the feedback window and enter question and answer information in the feedback window. The backend outputs corresponding result information based on the question and answer information.

[0198] The warehouse planning method provided in the embodiment of the present application can receive user satisfaction information, suggestion information and other needs corresponding to the final planning results by setting a feedback window on the user interaction interface, so as to provide users with more appropriate planning solutions and further improve user experience.

[0199] Fig. 9 A schematic diagram of a storage planning device provided in an embodiment of the present application is shown in FIG. Fig. 9 The storage planning device 900 includes an acquisition module 910, a splitting module 920, a processing module 930, a determination module 940 and a control module 950. Among them:

[0200] The acquisition module 910 is configured to: acquire the to-be-processed task input by the user in the user interaction interface.

[0201] The splitting module 920 is configured to split the task to be processed through the warehouse planning model to obtain at least one subtask.

[0202] The processing module 930 is configured to: analyze and process each subtask through the warehouse planning model to obtain at least one request information corresponding to each subtask.

[0203] Determination module 940 is configured to: determine the processing results corresponding to each subtask through the warehouse planning model in response to at least one feedback information input by the user for at least one request information corresponding to each subtask; and determine the planning results corresponding to the tasks to be processed through the warehouse planning model based on the processing results corresponding to each subtask in at least one subtask.

[0204] The control module 950 is configured to: control the user interaction interface to display each request information, and control the user interaction interface to display the planning result.

[0205] In some embodiments, the warehouse planning model includes a task splitting sub-model; the splitting module 920 is configured to: based on the complexity of the task to be processed and the preset splitting principle, split the task to be processed into at least one sub-task through the task splitting sub-model; wherein the preset splitting principle includes that the number of tasks of at least one sub-task is less than or equal to a preset number threshold and / or the correlation between any two sub-tasks in the at least one sub-task is less than or equal to a preset correlation threshold.

[0206] In some embodiments, the warehouse planning model includes a task execution sub-model; the processing module 930 is configured to: analyze and process the first sub-task based on the task execution sub-model to determine the first request information corresponding to the first sub-task. The control module 950 is configured to: control the user interaction interface to display the first request information; wherein at least one sub-task includes the first sub-task, and at least one request information corresponding to the first sub-task includes the first request information.

[0207] In some embodiments, the determination module 940 is configured to: in response to first feedback information input by a user for first request information corresponding to a first subtask, determine second request information corresponding to the first subtask through a task execution submodel; in response to second feedback information input by a user for the second request information, determine a first processing result corresponding to the first subtask through the task execution submodel based on the first feedback information and the second feedback information; wherein, at least one request information corresponding to the first subtask includes the second request information; and the control module 950 is configured to: control the user interaction interface to display the second request information.

[0208] In some embodiments, at least one subtask includes a first subtask and a second subtask, and the second subtask is the next task of the first subtask; after determining the first processing result corresponding to the first subtask, the determination module 940 is configured to: based on at least one feedback information corresponding to the first subtask, analyze and process the second subtask through the warehouse planning model, determine at least one request information corresponding to the second subtask, and in response to at least one feedback information input by the user for the at least one request information corresponding to the second subtask, determine the second processing result corresponding to the second subtask through the warehouse planning model. The control module 950 is configured to: control the user interaction interface to display the at least one request information corresponding to the second subtask.

[0209] In some embodiments, the determination module 940 is configured to: analyze and process the second subtask through the task execution submodel to obtain at least one request information corresponding to the second subtask; wherein the at least one request information corresponding to the second subtask includes third request information and fourth request information. The control module 950 is configured to: if there is feedback information corresponding to the third request information in the at least one feedback information corresponding to the first subtask, and there is no feedback information corresponding to the fourth request information in the at least one feedback information corresponding to the first subtask, then control the user interaction interface not to display the third request information and to display the fourth request information; if there is no feedback information corresponding to the third request information in the at least one feedback information corresponding to the first subtask, then control the user interaction interface to display the third request information.

[0210] In some embodiments, the determination module 940 is configured to: determine the planning result corresponding to the task to be processed through the task execution sub-model based on the first processing result and the second processing result. The control module 950 is configured to: control the user interaction interface to display the planning result.

[0211] In some embodiments, the warehouse planning model includes a task execution sub-model; the task execution sub-model includes a first execution network and a second execution network. The determination module 940 is configured to: determine the task target and preset algorithm library of the sub-task; based on the task target of the sub-task, the preset algorithm library, and at least one feedback information corresponding to the sub-task, determine the task execution information corresponding to the sub-task through the first execution network; wherein the task execution information is used to indicate the target execution method for achieving the task target of the sub-task; the preset algorithm library includes multiple algorithms, and the target execution method includes calling at least one algorithm in the preset algorithm library; based on the task execution information, determine the corresponding processing result of the sub-task through the second execution network.

[0212] In some embodiments, the task objective of the subtask includes determining an efficiency index of the warehousing system, and the target execution method includes calling an efficiency prediction model in a preset algorithm library.

[0213] In some embodiments, the determination module 940 is configured to: based on the task execution information and at least one feedback information corresponding to the subtask, generate a processing result corresponding to the subtask by calling the efficiency prediction model through the second execution network; wherein the processing result includes multiple sets of prediction information, and the multiple sets of prediction information are used to indicate the efficiency indicators corresponding to multiple sets of system parameters in the warehousing system.

[0214] In some embodiments, the efficiency prediction model includes a first prediction sub-model and a second prediction sub-model; the determination module 940 is configured to: determine the target input information based on at least one feedback information corresponding to the sub-task; wherein the target input information includes the warehouse size, handling equipment type and carrier handling efficiency corresponding to the warehousing system; process the target input information based on the first prediction sub-model to obtain the target configuration parameters of the warehousing system; wherein the target configuration parameters include the number of handling equipment and / or the number of workstations; perform similarity processing on the target configuration parameters through a preset similarity algorithm, and expand to obtain multiple groups of system configuration parameters; wherein the multiple groups of system configuration parameters include the target configuration parameters; process the multiple groups of system configuration parameters based on the second prediction sub-model to determine the efficiency indicators corresponding to each group of system configuration parameters; wherein the efficiency indicators include at least one of the workstation utilization rate, handling equipment utilization rate, task cycle time and number of vehicles of the warehousing system.

[0215] In some embodiments, at least one subtask includes a first subtask and a second subtask, and the second subtask is the next subtask of the first subtask; the warehouse planning model includes a task execution submodel and a task correction submodel. The warehouse planning device 900 also includes an optimization module, which is configured to: if the first processing result corresponding to the first subtask cannot be determined by the task execution submodel, or if the first processing result corresponding to the first subtask is determined to be abnormal by the task execution submodel, then the first subtask is optimized by the task correction submodel to obtain the optimized first subtask; wherein the optimization includes further splitting the first subtask, or adjusting the first subtask to re-determine at least one request information corresponding to the optimized first subtask by the task execution submodel. The processing module 930 is also configured to: if the confirmation information input by the user on the user interaction interface for the first processing result corresponding to the first subtask meets the end trigger condition corresponding to the first subtask, then the second subtask is analyzed and processed by the warehouse planning model.

[0216] In some embodiments, the determination module 940 is also configured to: if the confirmation information entered by the user on the user interaction interface for the first processing result does not meet the end trigger condition corresponding to the first subtask, then determine that there is an abnormality in the first processing result; or, if the number of times the user enters abnormal information on the user interaction interface for the first processing result exceeds a preset number threshold, then determine that there is an abnormality in the first processing result.

[0217] In some embodiments, at least one subtask includes a first subtask, and the warehouse planning model includes a task execution submodel and a result verification submodel. The warehouse planning device 900 also includes a verification module, which is configured to: based on at least one feedback information corresponding to the first subtask, verify the first processing result corresponding to the first subtask through the result verification submodel to obtain a verification result. The determination module 940 is also configured to: if the verification result is abnormal, re-analyze and process the first subtask through the task execution submodel, and re-determine the processing result corresponding to the first subtask.

[0218] In some embodiments, the user interaction interface includes a progress bar. The determination module 940 is further configured to: determine the progress information of each subtask in response to at least one feedback information input by the user for at least one request information corresponding to each subtask; and display the task completion degree of the pending task through the progress bar based on the progress information of each subtask.

[0219] In some embodiments, the user interaction interface includes an assistant window; the acquisition module 910 is further configured to: acquire at least one question and answer information for the planning result input by the user in the assistant window. The processing module 930 is further configured to: process the at least one question and answer information through the warehouse planning model; the control module 950 is further configured to: control the assistant window to display the result information corresponding to the question and answer information.

[0220] Fig.10 A schematic diagram of an electronic device provided in an embodiment of the present application. In some embodiments, the electronic device includes one or more processors and a memory. The memory is configured to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the warehouse planning method in the above embodiment.

[0221] like Fig.10 As shown, the electronic device 1000 includes: a processor (processor) 1001 and a memory 1002. Exemplarily, the electronic device 1000 may also include: a communication interface (Communications Interface) 1003 and a communication bus 1004.

[0222] The processor 1001, the memory 1002 and the communication interface 1003 communicate with each other via the communication bus 1004. The communication interface 1003 is used to communicate with other devices such as client or other server network elements.

[0223] In some embodiments, the processor 1001 is used to execute the program 1005, and specifically, the relevant steps in the above-mentioned storage planning method embodiment can be executed. Specifically, the program 1005 can include program code, and the program code includes computer executable instructions.

[0224] Exemplarily, the processor 1001 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The electronic device 1000 may include one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0225] In some embodiments, the memory 1002 is used to store the program 1005. The memory 1002 may include a high-speed RAM memory, and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0226] Program 1005 can be specifically called by processor 1001 to enable electronic device 1000 to execute operations of the warehouse planning method.

[0227] An embodiment of the present application provides a computer-readable storage medium, which stores at least one executable instruction. When the executable instruction is executed on the electronic device 1000, the electronic device 1000 executes the warehouse planning method in the above embodiment.

[0228] The executable instructions can be specifically used to enable the electronic device 1000 to perform operations of the warehouse planning method.

[0229] For example, the computer readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0230] In some embodiments, an embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the warehouse planning method described in any of the above embodiments.

[0231] In some embodiments, the embodiments of the present application further provide a computer program, which, when executed by a processor, can implement the warehouse planning method described in any of the above embodiments.

[0232] The beneficial effects that can be achieved by the warehouse planning device, electronic device, computer-readable storage medium, computer program product and computer program provided in the embodiments of the present application can refer to the beneficial effects of the warehouse planning method provided above, and will not be repeated here.

[0233] It should be noted that, in the application, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0234] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0235] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, which can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processor or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0236] For the purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by an instruction execution system, apparatus, or device or in conjunction with such instruction execution system, apparatus, or device.

[0237] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection having one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM).

[0238] In addition, the computer readable medium can even be a paper or other suitable medium on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, and then editing, interpreting or processing in other suitable ways as necessary, and then storing it in the computer memory. It should be understood that various parts of the present application can be implemented in hardware, software, firmware or a combination thereof.

[0239] In the above embodiments, multiple steps or methods may be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it may be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0240] The above-described embodiments of the present application do not constitute a limitation on the protection scope of the present application.

Claims

1. A warehouse planning method, characterized in that: The method comprises: Get the pending tasks entered by the user in the user interaction interface; Splitting the pending task through a warehouse planning model to obtain at least one subtask; Analyzing and processing each of the subtasks through the warehouse planning model to obtain at least one request information corresponding to each of the subtasks, and controlling the user interaction interface to display each of the request information; In response to at least one feedback information input by a user for at least one request information corresponding to each of the subtasks, determining a processing result corresponding to each of the subtasks through the warehouse planning model; Based on the processing results corresponding to each of the at least one subtask, the planning results corresponding to the task to be processed are determined through the warehouse planning model, and the user interaction interface is controlled to display the planning results.

2. The method according to claim 1, characterized in that: The warehouse planning model includes a task splitting sub-model, and the warehouse planning model is used to split the task to be processed to obtain at least one sub-task, including: Based on the complexity of the task to be processed and a preset splitting principle, splitting the task to be processed into the at least one subtask through the task splitting submodel; The preset splitting principle includes that the number of tasks of the at least one subtask is less than or equal to a preset number threshold and / or the correlation between any two subtasks in the at least one subtask is less than or equal to a preset correlation threshold.

3. The method according to claim 1, characterized in that The warehouse planning model includes a task execution sub-model, and each of the sub-tasks is analyzed and processed by the warehouse planning model to obtain at least one request information corresponding to each of the sub-tasks, and the user interaction interface is controlled to display each of the request information, including: The first subtask is analyzed and processed based on the task execution submodel, the first request information corresponding to the first subtask is determined, and the user interaction interface is controlled to display the first request information; wherein, the at least one subtask includes the first subtask, and the at least one request information corresponding to the first subtask includes the first request information.

4. The method according to claim 3, characterized in that The step of determining the processing result corresponding to each of the subtasks by the warehouse planning model in response to at least one feedback information input by the user for the at least one request information corresponding to each of the subtasks includes: In response to first feedback information input by a user for the first request information corresponding to the first subtask, determining second request information corresponding to the first subtask through the task execution submodel, and controlling the user interaction interface to display the second request information; wherein the at least one request information corresponding to the first subtask includes the second request information; In response to second feedback information input by the user in response to the second request information, a first processing result corresponding to the first subtask is determined through the task execution sub-model based on the first feedback information and the second feedback information.

5. The method according to claim 1, characterized in that The at least one subtask includes a first subtask and a second subtask, wherein the second subtask is the next task of the first subtask; After determining the first processing result corresponding to the first subtask, in response to at least one feedback information input by the user for the at least one request information corresponding to each subtask, determining the processing result corresponding to each subtask by using the warehouse planning model includes: Based on at least one feedback information corresponding to the first subtask, analyzing and processing the second subtask through the warehouse planning model, determining at least one request information corresponding to the second subtask, and controlling the user interaction interface to display the at least one request information corresponding to the second subtask; In response to at least one feedback information input by a user for at least one request information corresponding to the second subtask, a second processing result corresponding to the second subtask is determined through the warehouse planning model.

6. The method according to claim 5, characterized in that The step of analyzing and processing the second subtask based on the at least one feedback information corresponding to the first subtask by using the warehouse planning model, determining at least one request information corresponding to the second subtask, and controlling the user interaction interface to display the at least one request information corresponding to the second subtask includes: Analyze and process the second subtask through the task execution submodel to obtain at least one request information corresponding to the second subtask; wherein the at least one request information corresponding to the second subtask includes third request information and fourth request information; If there is feedback information corresponding to the third request information in at least one feedback information corresponding to the first subtask, and there is no feedback information corresponding to the fourth request information in at least one feedback information corresponding to the first subtask, controlling the user interaction interface not to display the third request information and to display the fourth request information; If there is no feedback information corresponding to the third request information in the at least one feedback information corresponding to the first subtask, controlling the user interaction interface to display the third request information.

7. The method according to claim 5, characterized in that The step of determining the planning result corresponding to the task to be processed by the warehouse planning model based on the processing result corresponding to each of the subtasks in the at least one subtask, and controlling the user interaction interface to display the planning result includes: Based on the first processing result and the second processing result, the planning result corresponding to the task to be processed is determined through the task execution sub-model, and the user interaction interface is controlled to display the planning result.

8. The method according to any one of claims 1 to 7, characterized in that The warehouse planning model includes a task execution sub-model, and the task execution sub-model includes a first execution network and a second execution network; in response to at least one feedback information input by a user for at least one request information corresponding to each sub-task, determining a processing result corresponding to each sub-task through the warehouse planning model includes: Determining the task objectives and preset algorithm library of the subtasks; Based on the task objective of the subtask, the preset algorithm library, and at least one feedback information corresponding to the subtask, the task execution information corresponding to the subtask is determined through the first execution network; wherein the task execution information is used to indicate a target execution method for achieving the task objective of the subtask; the preset algorithm library includes a plurality of algorithms, and the target execution method includes calling at least one algorithm in the preset algorithm library; Based on the task execution information, determining, through the second execution network, that the subtask corresponds to the processing result.

9. The method according to claim 8, characterized in that The task objective of the subtask includes determining the efficiency index of the warehousing system, and the target execution method includes calling the efficiency prediction model in the preset algorithm library.

10. The method according to claim 9, characterized in that The determining, based on the task execution information, through the second execution network, that the subtask corresponds to the processing result includes: Based on the task execution information and at least one feedback information corresponding to the subtask, the efficiency prediction model is called through the second execution network to generate the processing result corresponding to the subtask; wherein the processing result includes multiple groups of prediction information, and the multiple groups of prediction information are used to indicate the efficiency indicators corresponding to multiple groups of system parameters in the warehousing system.

11. The method according to claim 10, characterized in that The efficiency prediction model includes a first prediction sub-model and a second prediction sub-model; based on the task execution information and at least one feedback information corresponding to the sub-task, calling the efficiency prediction model through the second execution network to generate the processing result corresponding to the sub-task includes: Determine target input information based on at least one feedback information corresponding to the subtask; wherein the target input information includes warehouse size, handling equipment type and carrier handling efficiency corresponding to the warehousing system; Processing the target input information based on the first prediction sub-model to obtain target configuration parameters of the warehousing system; wherein the target configuration parameters include the number of handling equipment and / or the number of workstations; Performing similarity processing on the target configuration parameters by using a preset similarity algorithm, and expanding to obtain the multiple sets of system configuration parameters; wherein the multiple sets of system configuration parameters include the target configuration parameters; Based on the second prediction sub-model, the multiple groups of system configuration parameters are processed to determine the efficiency indicators corresponding to each group of system configuration parameters; wherein the efficiency indicators include at least one of the workstation utilization rate, handling equipment utilization rate, task cycle time, and number of carriers of the warehousing system.

12. The method according to any one of claims 1 to 7, characterized in that The at least one subtask includes a first subtask and a second subtask, wherein the second subtask is a next subtask of the first subtask; The warehouse planning model includes a task execution sub-model and a task correction sub-model, and the method further includes: If the first processing result corresponding to the first subtask cannot be determined through the task execution submodel, or if the first processing result corresponding to the first subtask is determined to be abnormal through the task execution submodel, the first subtask is optimized through the task correction submodel to obtain an optimized first subtask; wherein the optimization includes further splitting the first subtask, or adjusting the first subtask to re-determine at least one request information corresponding to the optimized first subtask through the task execution submodel; If the confirmation information input by the user on the user interaction interface for the first processing result corresponding to the first subtask meets the end trigger condition corresponding to the first subtask, the second subtask continues to be analyzed and processed through the warehouse planning model.

13. The method according to claim 12, characterized in that The method further comprises: If the confirmation information input by the user on the user interaction interface for the first processing result does not meet the end trigger condition corresponding to the first subtask, it is determined that the first processing result is abnormal; or, If the number of times the user inputs abnormal information for the first processing result on the user interaction interface exceeds a preset number threshold, it is determined that the first processing result is abnormal.

14. The method according to any one of claims 1 to 7, characterized in that The at least one subtask includes a first subtask, the warehouse planning model includes a task execution submodel and a result verification submodel, and the method further includes: Based on at least one feedback information corresponding to the first subtask, verify the first processing result corresponding to the first subtask through the result verification submodel to obtain a verification result; If the verification result is abnormal, the first subtask is re-analyzed and processed through the task execution sub-model, and the processing result corresponding to the first subtask is re-determined.

15. The method according to any one of claims 1 to 7, characterized in that The user interaction interface includes a progress bar; the method further includes: In response to at least one feedback information input by a user for at least one request information corresponding to each of the subtasks, determining progress information of each of the subtasks; Based on the progress information of each of the subtasks, the task completion degree of the task to be processed is displayed through the progress bar.

16. The method according to any one of claims 1 to 7, characterized in that The user interaction interface includes an assistant window, and the method further includes: Acquire at least one question and answer information regarding the planning result input by the user in the assistant window; The at least one question and answer information is processed through the warehouse planning model, and the assistant window is controlled to display result information corresponding to the question and answer information.

17. A storage planning device, characterized in that: include: An acquisition module is configured to acquire a task to be processed input by a user in a user interaction interface; A splitting module is configured to split the to-be-processed task through a warehouse planning model to obtain at least one subtask; A processing module is configured to analyze and process each of the subtasks through the warehouse planning model to obtain at least one request information corresponding to each of the subtasks; a determination module configured to determine, in response to at least one feedback information input by a user for at least one request information corresponding to each subtask, a processing result corresponding to each subtask through the warehouse planning model; Based on the processing results corresponding to each of the subtasks in the at least one subtask, determining the planning results corresponding to the task to be processed through the warehouse planning model; The control module is configured to control the user interaction interface to display each of the request information, and control the user interaction interface to display the planning result.

18. An electronic device, characterized in that: include: one or more processors and memory; The memory is configured to: store one or more programs; Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the warehouse planning method according to any one of claims 1-16.

19. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the warehouse planning method according to any one of claims 1-16 is implemented.

20. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the warehouse planning method according to any one of claims 1 to 16.

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