Logistics warehouse unloading time scheduling method and device, equipment and storage medium

Abstract

The application relates to a logistics warehouse unloading time scheduling method and device, computer equipment and a storage medium. The application can reduce offline coordination and management costs while meeting the needs of transportation and production, and help enterprises reduce costs and increase efficiency. The method comprises the following steps: obtaining original unloading time arrangement information of a platform of a logistics warehouse; determining a platform with unloading blockage according to an original unloading start time in the original unloading time arrangement information and an actual unloading time of each platform, and taking the platform with unloading blockage as a to-be-adjusted platform; obtaining an original unloading start time of a low-frequency logistics vehicle corresponding to the to-be-adjusted platform; determining an unloading time adjustable range for the low-frequency logistics vehicle according to the original unloading start time of the low-frequency logistics vehicle; determining a second unloading time of the low-frequency logistics vehicle according to the unloading time adjustable range; and instructing the to-be-adjusted platform to arrange the low-frequency logistics vehicle to perform unloading treatment at the second unloading time.

Description

Technical Field

[0001] This application relates to the field of logistics and transportation technology, and in particular to a method, apparatus, computer equipment, and storage medium for scheduling unloading time in a logistics warehouse. Background Technology

[0002] With the rapid development of the logistics industry and the increase in production capacity of automobile manufacturers, these manufacturers require increasingly efficient automotive parts transportation and scheduling capabilities. In the automotive production scheduling logistics system, inbound logistics is a crucial link in ensuring high production efficiency. Inbound logistics refers to the process of transporting automotive parts from various component suppliers to the automobile manufacturing plant and into the warehouse. The warehouse receiving stage is the final stage of inbound logistics. Warehouse receiving involves developing and executing unloading plans for all parts transport vehicles arriving at the automobile manufacturing plant, ensuring the rapid and orderly entry of all parts into the warehouse. This is a necessary prerequisite for ensuring the normal operation of automobile production.

[0003] In the current automotive production scheduling and logistics system, warehouse receiving plans typically employ three methods. The first is the FCFS (First Come First Service) algorithm, which determines the unloading order based on the arrival order of goods. This method can easily lead to long unloading times for trucks making short-distance trips and multiple round trips within a day. The second method is peak forecasting, which estimates the peak receiving capacity required by each warehouse platform. Platforms that cannot reach their peak capacity can be handled through offline coordination. This method increases manpower and material costs. The third method is flexible management, which dynamically adjusts the receiving capacity of each warehouse platform through certain management tools. This method requires extremely high offline management skills and is prone to chaos. It is evident that existing scheduling methods still suffer from inefficiency and high costs. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, and storage medium for scheduling unloading time in a logistics warehouse to address the aforementioned technical problems.

[0005] A method for scheduling unloading time in a logistics warehouse, the method comprising:

[0006] Obtain the original unloading schedule information for the logistics warehouse platform;

[0007] Based on the original unloading start time and the current actual unloading time of each platform in the original unloading time schedule information, the platforms with unloading blockages are identified and designated as platforms to be adjusted.

[0008] Obtain the original unloading start time of the low-frequency logistics vehicle corresponding to the platform to be adjusted;

[0009] Based on the original unloading start time of the low-frequency logistics vehicle and the preset adjustable upper and lower limits, the adjustable range of unloading time for the low-frequency logistics vehicle is determined; the adjustable range of unloading time ensures that the unloading time of the high-frequency logistics vehicle and the low-frequency logistics vehicle unloading at the platform to be adjusted meets the preset delivery speed.

[0010] The second unloading time of the low-frequency logistics vehicle is determined based on the adjustable unloading time range.

[0011] The platform to be adjusted is instructed to schedule the low-frequency logistics vehicle to unload cargo at the second unloading time.

[0012] In one embodiment, determining the second unloading time of the low-frequency logistics vehicle based on the adjustable unloading time range includes:

[0013] Determine whether there is a valid unloading time within the adjustable unloading time range; the valid unloading time is the unloading start time that can prevent the platform to be adjusted from unloading blockage;

[0014] If so, the optimal effective unloading time is selected from the effective unloading times as the second unloading time; wherein, the optimal effective unloading time is the time that minimizes the adjustment range of the original unloading start time of the low-frequency logistics vehicle.

[0015] In one embodiment, after determining whether there is a valid unloading time within the adjustable unloading time range, the method further includes:

[0016] If not, then find the minimum unloading time from the adjustable unloading time range; the minimum unloading time is the unloading start time that minimizes the unloading blockage time between the high-frequency logistics vehicle and the low-frequency logistics vehicle.

[0017] The second unloading time of the low-frequency logistics vehicle is determined based on the minimum unloading time of the blockage.

[0018] In one embodiment, the minimum unloading time for congestion includes multiple parameters; determining the second unloading time of the low-frequency logistics vehicle based on the minimum unloading time for congestion includes:

[0019] The optimal time is selected from multiple minimum unloading times for congestion as the second unloading time for the low-frequency logistics vehicle; the optimal time is the time that minimizes the adjustment range of the original unloading start time of the low-frequency logistics vehicle.

[0020] In one embodiment, after instructing the platform to be adjusted to schedule the low-frequency logistics vehicle for unloading at the second unloading time, the method further includes:

[0021] Update the status of the platform to be adjusted to the platform that has been adjusted.

[0022] If the adjusted platform still experiences unloading congestion, then determine the time distribution of the unloading congestion status within a preset time period.

[0023] The offline logistics guidance and prompts are determined based on the time distribution.

[0024] In one embodiment, determining the offline prompt information based on the time distribution status includes:

[0025] If the frequency of the unloading blockage occurs within a preset time period at a rate higher than the first preset rate and is concentrated within a preset rest time range, then the offline logistics guidance prompt information will be determined to extend working hours.

[0026] In one embodiment, determining the offline prompt information based on the time distribution status further includes:

[0027] If the time distribution state is a scattered state, then the offline logistics guidance prompt information is determined to dispatch forklift support; the scattered state means that there are multiple unloading blockage states in the time distribution state within a preset time period, and the occurrence frequency of each unloading blockage state is lower than the second preset proportion.

[0028] And / or,

[0029] If the time distribution state is a multiple high-occurrence state, then the offline logistics guidance prompt information is determined to be to increase the number of resident forklifts or increase the number of unloading stations; the multiple high-occurrence state refers to the existence of multiple unloading blockage states in the time distribution state within a preset time period, and the occurrence frequency of each unloading blockage state is higher than the third preset proportion.

[0030] A logistics warehouse unloading time scheduling device, the device comprising:

[0031] The first information acquisition module is used to acquire the original unloading time schedule information of the logistics warehouse platform;

[0032] The platform to be adjusted module is used to determine the platforms with unloading blockages based on the original unloading start time in the original unloading time arrangement information and the current actual unloading time of each platform, and to designate the platforms with unloading blockages as platforms to be adjusted.

[0033] The second information acquisition module is used to acquire the original unloading start time of the low-frequency logistics vehicle corresponding to the platform to be adjusted;

[0034] The adjustable range determination module is used to determine the adjustable range of unloading time for the low-frequency logistics vehicle based on the original unloading start time and the preset adjustable upper and lower limits; the adjustable range of unloading time ensures that the unloading time of the high-frequency logistics vehicle and the low-frequency logistics vehicle unloading at the platform to be adjusted meets the preset delivery speed.

[0035] The second unloading time determination module is used to determine the second unloading time of the low-frequency logistics vehicle based on the adjustable range of unloading time.

[0036] The unloading task instruction module is used to instruct the platform to be adjusted to schedule the low-frequency logistics vehicle to unload at the second unloading time.

[0037] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps in the above-described embodiment of the logistics warehouse unloading time scheduling method.

[0038] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps as described in the above embodiment of the logistics warehouse unloading time scheduling method.

[0039] The aforementioned logistics warehouse unloading time scheduling method, device, computer equipment, and storage medium acquire the original unloading time arrangement information of the logistics warehouse platforms; based on the original unloading start time and the current actual unloading time of each platform in the original unloading time arrangement information, identify platforms with unloading congestion and designate them as platforms to be adjusted; acquire the original unloading start time of the low-frequency logistics vehicles corresponding to the platforms to be adjusted; determine the adjustable range of unloading time for the low-frequency logistics vehicles based on the original unloading start time and preset adjustable upper and lower limits; the adjustable range of unloading time ensures that the unloading times of the high-frequency and low-frequency logistics vehicles unloading at the platforms to be adjusted meet a preset supply speed; determine a second unloading time for the low-frequency logistics vehicles based on the adjustable range of unloading time; and instruct the platforms to be adjusted to schedule the low-frequency logistics vehicles to unload at the second unloading time. This method can reduce offline coordination and management costs while meeting transportation and production needs, helping enterprises reduce costs and increase efficiency. Attached Figure Description

[0040] Figure 1 This is a diagram illustrating the application environment of a logistics warehouse unloading time scheduling method in one embodiment.

[0041] Figure 2 This is a flowchart illustrating a logistics warehouse unloading time scheduling method in one embodiment;

[0042] Figure 3 This is a flowchart illustrating the intelligent adjustment steps in one embodiment;

[0043] Figure 4 This is a schematic diagram of an offline prompting and guidance process in another embodiment;

[0044] Figure 5 This is a structural block diagram of a logistics warehouse unloading time scheduling device in one embodiment;

[0045] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] The logistics warehouse unloading time scheduling method provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 101 communicates with server 102 via a network. Terminal 101 is distributed across various loading docks in the logistics warehouse to collect information about currently unloading vehicles or display prompts. Terminal 101 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. Server 102 is used to manage the unloading data from all warehouse loading docks and can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0048] In one embodiment, such as Figure 2 As shown, a method for scheduling unloading time in a logistics warehouse is provided, which can be applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps:

[0049] Step S201: Obtain the original unloading time schedule information of the logistics warehouse platform.

[0050] The original unloading time schedule information refers to the original unloading time schedule of each platform. Each platform is scheduled according to the ideal unloading time schedule, which means that it is assumed that each logistics vehicle can unload immediately upon arrival according to the schedule information and there is no unloading congestion.

[0051] Specifically, server 102 retrieves the original unloading schedule information for all loading docks in the logistics warehouse from the database. This original unloading schedule information includes the planned start time and unloading time period for each logistics vehicle.

[0052] Step S202: Based on the original unloading start time and the current actual unloading time of each platform in the original unloading time arrangement information, determine the platforms with unloading blockages and designate the platforms with unloading blockages as platforms to be adjusted.

[0053] Among them, unloading congestion refers to the situation where there is a conflict in unloading. For example, truck A was originally scheduled to start unloading at 10:00, and truck B was originally scheduled to start unloading at 10:10. However, due to some reason, truck A had not finished unloading at 10:10, which led to a conflict in unloading time between truck B and truck A.

[0054] Specifically, server 102 obtains the actual unloading time of each platform, compares and analyzes it with the original unloading start time in the original unloading time schedule information, calculates the platforms with unloading blockages, and marks the platform as a platform to be adjusted, that is, changes the status of the platform to a platform to be adjusted in the system.

[0055] Step S203: Obtain the original unloading start time of the low-frequency logistics vehicle corresponding to the platform to be adjusted.

[0056] Specifically, this application adopts a strategy of prioritizing high-frequency scheduling and intelligently adjusting low-frequency operations for intelligent dispatching. High-frequency and low-frequency are defined based on the actual logistics model. Currently, the commonly used delivery model in logistics transportation is the Milk Run model or the levelized production model, which involves cyclical pickup. The carrier carries goods that need to be returned from the customer to the supplier, arrives at each supplier sequentially, unloads the returned goods, loads goods to be collected from the supplier, and returns to the customer. The low-frequency logistics vehicle operates on a pre-set transportation route with a lower frequency than the high-frequency logistics vehicle on the same route. In practical scenarios, the frequency of a logistics vehicle is defined as the number of trips it makes on the route. For example, if truck A operates on route 1 and needs to make 9 trips within a specified time unit, then truck A's frequency is 9. In practical applications, low-frequency logistics vehicles and high-frequency logistics vehicles can be defined. The low-frequency logistics vehicles have a lower transportation frequency on the preset transportation route than the high-frequency logistics vehicles on the preset transportation route. Server 102 queries the original unloading start time of the low-frequency logistics vehicle corresponding to the platform to be adjusted.

[0057] Step S204: Based on the original unloading start time of the low-frequency logistics vehicle and the preset adjustable upper and lower limits, determine the adjustable range of the unloading time for the low-frequency logistics vehicle; the adjustable range of the unloading time ensures that the unloading time of the high-frequency logistics vehicle and the low-frequency logistics vehicle unloading at the platform to be adjusted meets the preset delivery speed.

[0058] The adjustable unloading time range is determined by the original unloading start time of the low-frequency logistics vehicle and the preset adjustable upper and lower limits. The preset adjustable upper and lower limits refer to the maximum range by which the original unloading start time of the low-frequency vehicle can be advanced or delayed. For example, the upper limit is +10 minutes, which means that it can be delayed by up to 10 minutes, and the lower limit is -10 minutes, which means that the maximum movement range is 10 minutes advanced. The preset adjustable upper and lower limits can be set in advance by humans.

[0059] Specifically, server 102 determines the adjustable range of unloading time for low-frequency logistics vehicles based on their original unloading start time and preset adjustable upper and lower limits. This ensures that adjusting the unloading start time within this adjustable range guarantees a certain supply speed. This supply speed refers to ensuring that the production efficiency of the manufacturing plant, such as an automobile manufacturer, meets preset production standards, such as completing the production of X vehicles per day. If the adjustment range exceeds this threshold, it may lead to a shortage of goods in the warehouse. When tires are needed to assemble automobiles, there may not be enough tires available, thus reducing the production efficiency of the manufacturing industry.

[0060] Step S205: Determine the second unloading time for low-frequency logistics vehicles based on the adjustable unloading time range.

[0061] Specifically, server 102 determines the second unloading time for low-frequency logistics vehicles based on the aforementioned adjustable unloading time range. For example, if the upper limit is +10 minutes, the second unloading time can be set 10 minutes later than the original unloading start time. Alternatively, a time can be selected within the aforementioned 10-minute range as the second unloading time, for example, it can be set 5 minutes later.

[0062] Step 206: Instruct the platform to be adjusted to arrange low-frequency logistics vehicles to unload goods at the second unloading time.

[0063] Specifically, the server 102 instructs the terminal 101 to perform the unloading task based on the above settlement result. For example, it may instruct low-frequency logistics vehicles to unload at the second unloading time and high-frequency logistics vehicles to unload at the first unloading time. Both the first unloading time and the second unloading time are adjusted actual unloading times.

[0064] The above embodiment involves: obtaining the original unloading time schedule information of the logistics warehouse platforms; identifying platforms with unloading congestion based on the original unloading start time and the current actual unloading time of each platform, and designating these platforms as platforms to be adjusted; obtaining the original unloading start time of the low-frequency logistics vehicles corresponding to the platforms to be adjusted; determining an adjustable range for the unloading time of the low-frequency logistics vehicles based on their original unloading start time and preset adjustable upper and lower limits; ensuring that the unloading times of both high-frequency and low-frequency logistics vehicles unloading at the platforms to be adjusted meet a preset supply speed; determining a second unloading time for the low-frequency logistics vehicles based on the adjustable range; and instructing the platforms to be adjusted to schedule the low-frequency logistics vehicles to unload at the second unloading time. This method can reduce platform congestion, meeting transportation and production needs while reducing offline coordination and management costs, thus helping enterprises reduce costs and increase efficiency.

[0065] In one embodiment, such as Figure 3 As shown, Figure 3 A flowchart illustrating the intelligent adjustment process for a platform to be adjusted is shown. Step S205 includes:

[0066] Determine whether there is an effective unloading time within the adjustable unloading time range; the effective unloading time is the unloading start time that can prevent unloading blockage at the platform to be adjusted; if so, select the best effective unloading time from the effective unloading time as the second unloading time; where the best effective unloading time is the time that minimizes the adjustment range of the original unloading start time of low-frequency logistics vehicles.

[0067] Specifically, after determining the preset adjustable upper and lower limits, server 102 needs to find a time (i.e., an effective unloading time) within the adjustable unloading time range determined by the preset adjustable upper and lower limits. For example, if the preset adjustable upper and lower limits are +10 and -10, then the adjustable unloading time range determined by the preset adjustable upper and lower limits is [-10, +10]. However, there may be time points within this range where unloading congestion cannot be avoided. For example, delaying by 5 minutes may still not avoid congestion, so a delay of 8 or 9 minutes is required. Therefore, the time after delaying the original unloading start time by 8 or 9 minutes is taken as the effective unloading time. The server uses a greedy algorithm to determine if the above effective unloading time exists, and then needs to select the best effective unloading time from it. The best effective unloading time is the unloading start time with the smallest required movement. For example, selecting the unloading start time delayed by 8 minutes is taken as the best effective unloading time. This best effective unloading time is the second unloading time for low-frequency logistics vehicles (i.e., the adjusted actual unloading start time).

[0068] In the above embodiments, based on the cyclical pickup characteristics required by the Milk Run transportation mode and the standardized production mode, low-frequency trucks have a wider range of optional unloading times. Prioritizing high-frequency routes and adjusting the unloading times of low-frequency trucks can reduce the risk of disrupting transportation plans due to changes in the unloading times of high-frequency routes. Furthermore, the adjustment time for low-frequency logistics vehicles can be adjusted forward or backward, rather than simply waiting for high-frequency trucks to finish unloading, thus maximizing the use of existing unloading resources at the platform and reducing the workload of offline coordination and management.

[0069] In one embodiment, combined with Figure 3 After determining whether there is a valid unloading time within the adjustable unloading time range, the following steps are also included:

[0070] If not, then find the minimum unloading time within the adjustable unloading time range; the minimum unloading time is the unloading start time that minimizes the unloading congestion time for both high-frequency and low-frequency logistics vehicles; based on the minimum unloading time, determine the second unloading time for low-frequency logistics vehicles.

[0071] Specifically, if an effective unloading time that can completely avoid unloading congestion cannot be found within the adjustable range of unloading time that can guarantee the preset production standard, then the unloading time with the minimum congestion is sought. The unloading start time that minimizes the time interval between unloading time conflicts is calculated using a greedy algorithm. For example, if vehicle A's unloading start time is 10:00 and it takes 10 minutes to unload, and vehicle B was originally scheduled to start unloading at 10:10, but in reality, vehicle A took 20 minutes to unload and could not finish until 10:20, then delaying vehicle B by 5 minutes cannot avoid the conflict. At the same time, the maximum threshold that can be moved is +10 minutes (this is just a simple example; in reality, the times of multiple low-frequency vehicles need to be adjusted simultaneously to minimize time conflicts). Therefore, unloading congestion cannot be completely avoided in this situation. In this case, it is necessary to calculate the unloading start time that minimizes the congestion time (using a greedy algorithm), and use this minimum congestion unloading time as the second unloading time for low-frequency logistics vehicles.

[0072] In the above embodiments, when unloading conflicts cannot be completely avoided, the minimum unloading time that minimizes time conflicts is calculated, thereby further improving unloading efficiency.

[0073] In one embodiment, combined with Figure 3 If the aforementioned minimum unloading time for congestion includes multiple parameters, then determining the second unloading time of the low-frequency logistics vehicle based on the aforementioned minimum unloading time for congestion includes:

[0074] The optimal time is selected from multiple minimum unloading times to serve as the second unloading time for low-frequency logistics vehicles; the optimal time is the time that minimizes the adjustment range of the original unloading start time of low-frequency logistics vehicles.

[0075] Specifically, if there are multiple minimum unloading times for the aforementioned blockage, then the unloading time with the smallest required movement value is selected from among the multiple unloading times with the least conflict, which is the actual unloading time, i.e., the comprehensive optimal time.

[0076] The above embodiments select the optimal unloading time from multiple minimum unloading times for congestion, further improving operational efficiency.

[0077] Furthermore, the aforementioned logistics warehouse unloading time scheduling method adopts a high-frequency truck priority strategy for two trucks with unloading time conflicts at the platform, adjusting the unloading time of the truck with the relatively lower frequency of unloading. The adjustment method does not wait for the high-frequency truck to finish unloading, but rather employs an intelligent adjustment strategy. This intelligent adjustment strategy is as follows: the unloading time can be adjusted backward to wait for the high-frequency truck to finish unloading, or it can be adjusted forward to complete unloading before the high-frequency truck begins unloading. However, the adjustment range is limited, and it is necessary to ensure that the adjusted unloading time of the low-frequency truck still meets transportation and production needs. When both forward and backward adjustments are possible, a greedy algorithm is used, prioritizing reducing unloading time conflicts and then minimizing the magnitude of unloading time adjustments as optimization objectives, ultimately selecting the final adjustment method. Compared to traditional solutions, this method makes fuller use of the platform's existing unloading resources and reduces the workload of offline coordination and management.

[0078] In one embodiment, such as Figure 4 As shown, Figure 4 The flowchart of offline guidance is shown. After step S206, the following steps are also included: updating the status of the platform to be adjusted to the platform that has been adjusted; if there is still unloading blockage on the platform that has been adjusted, then determining the time distribution of the unloading blockage status within a preset time period; and determining the offline logistics guidance information based on the time distribution status.

[0079] Specifically, after server 102 adjusts the aforementioned platform to be adjusted, it instructs the platform to execute according to the adjusted time. If unloading congestion still exists at this time, offline prompts are used for management. The server updates the status of the aforementioned platform to be adjusted to "adjusted platform". During execution, if the server detects that the adjusted platform is still in a congested state, it determines what kind of prompt should be given based on the time distribution of the unloading congestion status within a preset time period (e.g., the current day).

[0080] The above embodiments reduce platform congestion after intelligent adjustments, so only small-scale local coordination is needed. That is, offline prompts are provided to help resolve congestion and further improve unloading efficiency.

[0081] In one embodiment, such as Figure 4 As shown, the offline prompt information determined based on the time distribution status includes:

[0082] If the frequency of unloading congestion within a preset time period is higher than the first preset percentage and concentrated within the preset rest time range, then the offline logistics guidance prompt information will be determined to extend working hours.

[0083] And / or,

[0084] If the time distribution is in a scattered state, then the offline logistics guidance prompt information is determined to dispatch forklift support; the scattered state means that there are multiple unloading blockage states in the time distribution state within the preset time period, and the frequency of each unloading blockage state is lower than the second preset percentage.

[0085] And / or,

[0086] If the time distribution status is a multiple high-occurrence status, then the offline logistics guidance prompts will be to increase the number of resident forklifts or increase the number of unloading stations. A multiple high-occurrence status means that there are multiple unloading blockage statuses in the time distribution status within a preset time period, and the frequency of each unloading blockage status is higher than the third preset percentage.

[0087] Specifically, the server obtains the time distribution of unloading conflicts within a preset time period. If the conflict time is close to the preset rest time, for example, if the frequency of unloading blockage within the preset time period (e.g., the day) is higher than 30% (first preset percentage), the server instructs the terminal 101 to provide logistics guidance prompts, which may extend working hours.

[0088] Optionally, if the aforementioned unloading congestion mainly occurs during preset rest periods, and the number of logistics vehicles experiencing unloading time conflicts is less than a preset number (e.g., less than 10 vehicles), the terminal 101 can be instructed to provide logistics guidance prompts, which may include extending working hours.

[0089] If unloading blockages are scattered throughout a preset time period (e.g., the same day), the offline logistics guidance message will be to temporarily dispatch forklifts to assist before the conflict time. The aforementioned scattered blockages refer to the existence of multiple unloading blockages within the time distribution of the preset time period (e.g., the same day), and the frequency of each unloading blockage is lower than the second preset percentage (e.g., 20%).

[0090] If the above time distribution status is a high-frequency status, that is, there are multiple unloading blockage statuses in the time distribution status within the preset time period (e.g., the day) and the frequency of occurrence of each unloading blockage status is higher than the third preset percentage (e.g., 25%), then the offline logistics guidance prompt information is determined to be to add a resident forklift to the platform or to increase the number of unloading stations at the platform.

[0091] Alternatively, the above prompt information can also be retrieved from other unloading resources at the platform.

[0092] The above embodiments provide offline prompts in a localized manner, enabling flexible management without relying excessively on human judgment and allocation, thus reducing management difficulty and costs.

[0093] It should be understood that, although Figure 1-4 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1-4 At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0094] In one embodiment, such as Figure 5 As shown, a logistics warehouse unloading time scheduling device 500 is provided, including: a first information acquisition module 501, a platform to be adjusted determination module 502, a second information acquisition module 503, an adjustable range determination module 504, a second unloading time determination module 505, and an unloading task indication module 506, wherein:

[0095] The first information acquisition module 501 is used to acquire the original unloading time schedule information of the platform of the logistics warehouse;

[0096] The platform to be adjusted determination module 502 is used to determine the platforms with unloading blockages based on the original unloading start time and the current actual unloading time of each platform in the original unloading time arrangement information, and to designate the platforms with unloading blockages as platforms to be adjusted.

[0097] The second information acquisition module 503 is used to acquire the original unloading start time of the low-frequency logistics vehicle corresponding to the platform to be adjusted;

[0098] The adjustable range determination module 504 is used to determine the adjustable range of unloading time for the low-frequency logistics vehicle based on the original unloading start time and the preset adjustable upper and lower limits; the adjustable range of unloading time ensures that the unloading time of the high-frequency logistics vehicle and the low-frequency logistics vehicle unloading at the platform to be adjusted meets the preset supply speed.

[0099] The second unloading time determination module 505 is used to determine the second unloading time of the low-frequency logistics vehicle based on the adjustable range of unloading time.

[0100] The unloading task instruction module 506 is used to instruct the platform to be adjusted to schedule the low-frequency logistics vehicle to unload at the second unloading time.

[0101] In one embodiment, the second unloading time determination module 505 is further configured to: determine whether there is an effective unloading time within the adjustable range of unloading time; the effective unloading time is the unloading start time that enables the platform to be adjusted to avoid unloading blockage; if so, select the optimal effective unloading time from the effective unloading time as the second unloading time; wherein, the optimal effective unloading time is the time that minimizes the adjustment range of the original unloading start time of the low-frequency logistics vehicle.

[0102] In one embodiment, the second unloading time determination module 505 is further configured to: if not, find the minimum unloading time from the adjustable unloading time range; the minimum unloading time is the unloading start time that minimizes the unloading blockage time between the high-frequency logistics vehicle and the low-frequency logistics vehicle; and determine the second unloading time of the low-frequency logistics vehicle based on the minimum unloading time.

[0103] In one embodiment, the minimum unloading time for congestion includes multiple times; the second unloading time determination module 505 is further configured to: select the optimal time from the multiple minimum unloading times for congestion as the second unloading time of the low-frequency logistics vehicle; the optimal time is the time that minimizes the adjustment range of the original unloading start time of the low-frequency logistics vehicle.

[0104] In one embodiment, the unloading task instruction module 506 is further configured to: update the status of the platform to be adjusted to the adjusted platform; if the adjusted platform still has unloading blockage, determine the time distribution status of the unloading blockage status within a preset time period; and determine offline logistics guidance prompts based on the time distribution status.

[0105] In one embodiment, the unloading task indication module 506 is further configured to: if the frequency of the unloading blockage within a preset time period is higher than the first preset percentage and concentrated within a preset rest time range, then determine that the offline logistics guidance prompt information is to extend the working time.

[0106] In one embodiment, the unloading task instruction module 506 is further configured to: if the time distribution state is a scattered state, determine that the offline logistics guidance prompt information is to dispatch forklift support; the scattered state refers to the existence of multiple unloading blockage states in the time distribution state within a preset time period, and the occurrence frequency of each unloading blockage state is lower than the second preset proportion.

[0107] And / or,

[0108] If the time distribution state is a multiple high-occurrence state, then the offline logistics guidance prompt information is determined to be to increase the number of resident forklifts or increase the number of unloading stations; the multiple high-occurrence state refers to the existence of multiple unloading blockage states in the time distribution state within a preset time period, and the occurrence frequency of each unloading blockage state is higher than the third preset proportion.

[0109] Specific limitations regarding the logistics warehouse unloading time scheduling device can be found in the limitations of the logistics warehouse unloading time scheduling method described above, and will not be repeated here. Each module in the aforementioned logistics warehouse unloading time scheduling device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0110] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores raw unloading schedule information and adjusted schedule data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a logistics warehouse unloading time scheduling method.

[0111] Those skilled in the art will understand that Figure 6The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0112] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps as described in the above embodiment of the logistics warehouse unloading time scheduling method.

[0113] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the logistics warehouse unloading time scheduling method embodiment described above.

[0114] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0115] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for scheduling unloading time in a logistics warehouse, characterized in that, The method includes: Obtain the original unloading schedule information for the logistics warehouse platform; Based on the original unloading start time and the current actual unloading time of each platform in the original unloading time schedule information, the platforms with unloading blockages are identified and designated as platforms to be adjusted. Obtain the original unloading start time of the low-frequency logistics vehicle corresponding to the platform to be adjusted; Based on the original unloading start time of the low-frequency logistics vehicle and the preset adjustable upper and lower limits, the adjustable range of unloading time for the low-frequency logistics vehicle is determined; the adjustable range of unloading time ensures that the unloading time of both the high-frequency logistics vehicle and the low-frequency logistics vehicle unloading at the platform to be adjusted meets the preset delivery speed; the transportation frequency of the low-frequency logistics vehicle on the preset transportation route is lower than that of the high-frequency logistics vehicle on the preset transportation route. Based on the adjustable unloading time range, the second unloading time of the low-frequency logistics vehicle is determined; the second unloading time can prevent the platform to be adjusted from unloading blockage, or the second unloading time can minimize the unloading blockage time between the high-frequency logistics vehicle and the low-frequency logistics vehicle. The platform to be adjusted is instructed to schedule the low-frequency logistics vehicle to unload cargo at the second unloading time.

2. The method according to claim 1, characterized in that, The step of determining the second unloading time of the low-frequency logistics vehicle based on the adjustable unloading time range includes: Determine whether there is a valid unloading time within the adjustable unloading time range; wherein, the valid unloading time is the unloading start time that enables the platform to be adjusted to avoid unloading blockage; If so, the optimal effective unloading time is selected from the effective unloading times as the second unloading time; wherein, the optimal effective unloading time is the time that minimizes the adjustment range of the original unloading start time of the low-frequency logistics vehicle.

3. The method according to claim 2, characterized in that, After determining whether there is a valid unloading time within the adjustable unloading time range, the method further includes: If not, then find the minimum unloading time from the adjustable unloading time range; the minimum unloading time is the unloading start time that minimizes the unloading blockage time between the high-frequency logistics vehicle and the low-frequency logistics vehicle. The second unloading time of the low-frequency logistics vehicle is determined based on the minimum unloading time of the blockage.

4. The method according to claim 3, characterized in that, The minimum unloading time for congestion includes multiple parameters; determining the second unloading time for the low-frequency logistics vehicle based on the minimum unloading time for congestion includes: The optimal time is selected from multiple minimum unloading times for congestion as the second unloading time for the low-frequency logistics vehicle; the optimal time is the time that minimizes the adjustment range of the original unloading start time of the low-frequency logistics vehicle.

5. The method according to any one of claims 1 to 4, characterized in that, After instructing the platform to be adjusted to schedule the low-frequency logistics vehicle for unloading at the second unloading time, the method further includes: Update the status of the platform to be adjusted to the platform that has been adjusted. If the adjusted platform still experiences unloading congestion, then determine the time distribution of the unloading congestion status within a preset time period. The offline logistics guidance and prompts are determined based on the time distribution.

6. The method according to claim 5, characterized in that, Determining the offline prompt information based on the time distribution status includes: If the frequency of the unloading blockage occurs within a preset time period at a rate higher than the first preset rate and is concentrated within a preset rest time range, then the offline logistics guidance prompt information will be determined to extend working hours.

7. The method according to claim 5, characterized in that, The step of determining the offline prompt information based on the time distribution status also includes: If the time distribution state is a scattered state, then the offline logistics guidance prompt information is determined to dispatch forklift support; the scattered state means that there are multiple unloading blockage states in the time distribution state within a preset time period, and the occurrence frequency of each unloading blockage state is lower than the second preset proportion. And / or, If the time distribution state is a multiple high-occurrence state, then the offline logistics guidance prompt information is determined to be to increase the number of resident forklifts or increase the number of unloading stations; the multiple high-occurrence state refers to the existence of multiple unloading blockage states in the time distribution state within a preset time period, and the occurrence frequency of each unloading blockage state is higher than the third preset proportion.

8. A logistics warehouse unloading time scheduling device, characterized in that, The device includes: The first information acquisition module is used to acquire the original unloading time schedule information of the logistics warehouse platform; The platform to be adjusted module is used to determine the platforms with unloading blockages based on the original unloading start time in the original unloading time arrangement information and the current actual unloading time of each platform, and to designate the platforms with unloading blockages as platforms to be adjusted. The second information acquisition module is used to acquire the original unloading start time of the low-frequency logistics vehicle corresponding to the platform to be adjusted; The adjustable range determination module is used to determine the adjustable range of unloading time for the low-frequency logistics vehicle based on the original unloading start time and the preset adjustable upper and lower limits; the adjustable range of unloading time ensures that the unloading time of both the high-frequency logistics vehicle and the low-frequency logistics vehicle unloading at the platform to be adjusted meets the preset delivery speed; the transportation frequency of the low-frequency logistics vehicle on the preset transportation route is lower than that of the high-frequency logistics vehicle on the preset transportation route. The second unloading time determination module is used to determine the second unloading time of the low-frequency logistics vehicle based on the adjustable range of unloading time; the second unloading time can enable the platform to be adjusted to avoid unloading blockage, or the second unloading time can minimize the unloading blockage time between the high-frequency logistics vehicle and the low-frequency logistics vehicle. The unloading task instruction module is used to instruct the platform to be adjusted to schedule the low-frequency logistics vehicle to unload at the second unloading time.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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