Warehouse resource allocation-oriented intelligent decision-making system and method

Abstract

The invention relates to the technical field of warehouse intelligent management, in particular to an intelligent decision-making system and method for warehouse resource allocation, and the system comprises an information obtaining unit, an information processing unit, a model unit, a problem solving unit, a feedback unit, a tracking unit, a security unit and an optimization unit. The output end of the information acquisition unit is in communication connection with the input end of the information processing unit, the output end of the information processing unit is in communication connection with the input end of the model unit, and the output end of the model unit is in communication connection with the input end of the problem solving unit. The output end of the problem solving unit is in communication connection with the input end of the feedback unit; after the decision scheme is generated, the decision scheme can be input into the model unit to be verified, whether the generated decision scheme meets the requirement of warehouse resource allocation or not is ensured, and the situations that the error between the decision scheme and an actual warehouse resource allocation scheme is large, and warehouse resource allocation is wrong are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse intelligent management, and in particular to an intelligent decision-making system and method for warehouse resource allocation. Background Art

[0002] Warehouse resource management plays a vital role in modern industry. The production, operation and planning and scheduling of enterprises mainly rely on the decision-making of enterprise managers based on their long-term accumulated experience and relevant process knowledge. In addition, manual decision-making is arbitrary and lacks timeliness and accuracy, which often causes the comprehensive production indicators of enterprises to deviate from the predetermined target range, resulting in problems such as warehouse cargo accumulation or insufficient resource allocation. When market demand and production factor conditions change frequently or drastically, it is difficult to make timely and accurate decision responses based on manual experience and knowledge, thus making it impossible to achieve efficient management of enterprise warehouses. In order to solve this problem, an intelligent decision-making system has been designed through AI technology to assist in the decision-making of warehouse resource allocation.

[0003] For example, an intelligent decision-making system and method for warehouse resource allocation with application number CN202111439904.0 and publication date 20220325, for allocation problems such as excess storage and insufficient supply of warehouse resources, uses machine learning methods to predict future demand based on existing demand data, and predicts demand data combined with reinforcement learning self-learning capabilities to realize warehouse resource decision-making management, aiming to improve the utilization rate of warehouse resources and reduce resource maintenance costs. The present invention weakens the subjective decision-making effect of humans in dynamic market changes, and can improve the utilization rate of warehouse resources and reduce resource maintenance costs.

[0004] The warehouse resource allocation intelligent decision-making system on the market can achieve the optimal decision for warehouse resources through self-learning ability during the decision-making process, but lacks verification in the decision-making process. There will still be large errors in actual application, resulting in errors in warehouse resource allocation. Therefore, it is urgent to design an intelligent decision-making system and method for warehouse resource allocation to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent decision-making system and method for warehouse resource allocation to solve the above-mentioned deficiencies in the prior art.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent decision-making system for warehouse resource allocation, including an information acquisition unit, an information processing unit, a model unit, a problem-solving unit, a feedback unit, a tracking unit, a security unit, and an optimization unit. The output end of the information acquisition unit is communicatively connected to the input end of the information processing unit. The output end of the information processing unit is communicatively connected to the input end of the model unit. The output end of the model unit is communicatively connected to the input end of the problem-solving unit. The output end of the problem-solving unit is communicatively connected to the input end of the feedback unit.

[0008] The information acquisition unit is used to acquire warehouse resource allocation data. The information acquisition unit is connected to the warehouse management system through a network port. The warehouse resource allocation data acquired by the information acquisition unit includes the total quantity of warehouse resources in a production cycle, the allocation quantity of warehouse resources in a production cycle, and the guaranteed quantity of warehouse resources in a production cycle.

[0009] The model unit is used to analyze and calculate the data processed by the information processing unit. The model unit is divided into a calculation module and a prediction module. The calculation module is constructed based on the warehouse resource supply-demand formula, and the supply-demand formula is as follows:

[0010]

[0011] Among them, S i (i = 1, 2, 3... n) is the supply-demand ratio of the i-th type of warehouse resource in a production cycle. is the total allocation quantity of the i-th type of warehouse resource in a production cycle, and M i (i = 1, 2, 3... n) is the total quantity of the i-th type of warehouse resource in a production cycle. There is no need to supplement the quantity of warehouse resources. When, it is necessary to supplement the quantity of warehouse resources. is the maximum supply-demand ratio of the guaranteed material allocation of the i-th type of warehouse resource in a production cycle.

[0012] The prediction module is constructed through the warehouse resource allocation speed formula, and the warehouse resource allocation rate formula is as follows:

[0013]

[0014] Among them, is the average allocation quantity of the i-th type of warehouse resource in a production cycle. is the total allocation quantity of the i-th type of warehouse resource in a production cycle. If There is no need to allocate additional quantity of the i-th type of warehouse resource. If The quantity of the i-th type of warehouse resources needs to be additionally allocated.

[0015] The information processing unit is used to process the data acquired by the information acquisition unit. The information processing unit includes an identification module, a classification and summarization module, and a correlation module. The identification module identifies the warehouse resource allocation data acquired by the information acquisition unit by the category of warehouse resources. The classification and summarization module classifies and summarizes the acquired warehouse resource allocation data according to the results identified by the identification module. The correlation module performs correlation analysis and processing on the data summarized by the classification and summarization module according to the requirements of product production. The specific steps are as follows:

[0016] S1-1. Confirm various warehouse resources required by product production requirements.

[0017] S1-2. Summarize the data summarized by the classification and summarization module again according to the confirmed warehouse resources for product production.

[0018] S1-3. Generate a corresponding warehouse resource allocation list for the product according to the summarization result.

[0019] The problem-solving unit generates a decision-making plan according to the analysis result of the model unit and verifies the decision-making plan. The problem-solving unit includes an AI module, a detection module, and a screening module. The AI module searches for the decision-making plans of the previous resource allocation in the warehouse through keyword search technology. The AI module also searches for the resource allocation plans on the Internet through keyword search technology. The detection module is used to input the plans searched by the AI module into the model unit for calculation. The screening module screens out 3-5 optimal decision-making plans according to the results detected by the detection module.

[0020] The feedback unit is used to transmit the decision-making plan generated by the problem-solving unit to the warehouse management personnel. The feedback unit is established through text information push technology. The feedback unit transmits the decision-making plan generated by the problem-solving unit to the warehouse administrator by means of SMS, email, and WeChat push.

[0021] The tracking unit is used to track the materials flowing out of the warehouse. The tracking unit is used to track the transfer process after the warehouse resources are allocated. The tracking unit is established by using RFID (Radio Frequency Identification) technology.

[0022] The security unit is used to ensure the security of the decision-making system. The security unit adopts one of 360 network protection and Huorong protection.

[0023] The optimization unit is used to optimize the decision-making system. The optimization unit is established based on deep learning technology. The optimization unit processes the decision-making system in five ways: algorithm optimization, hardware optimization, parallel computing, model optimization, and data processing.

[0024] An intelligent decision-making method for warehouse resource allocation includes the following steps:

[0025] Step S1. Obtain past warehouse resource allocation data and classify and summarize the obtained data;

[0026] Step S2. Analyze the classified data and construct a warehouse resource supply and demand formula and a warehouse resource allocation speed formula;

[0027] Step S3. Through data analysis, construct a decision-making system and divide the decision-making system into eight functional areas: an information acquisition unit, an information processing unit, a model unit, a problem-solving unit, a feedback unit, a tracking unit, a security unit, and an optimization unit;

[0028] Step S4. Connect the decision-making system with the warehouse management system, and the decision-making system can obtain warehouse resource data in real time;

[0029] Step S5. The decision-making system analyzes and calculates the obtained warehouse resource data, and automatically generates a decision-making plan according to the calculation results to manage the allocation of warehouse resources.

[0030] In the above technical solution, the intelligent decision-making system and method for warehouse resource allocation provided by the present invention have the following beneficial effects:

[0031] (1) After the intelligent decision-making system designed by the present invention generates a decision-making plan, it can also input the decision-making plan into the model unit for verification to ensure whether the generated decision-making plan meets the requirements of warehouse resource allocation, and avoid the situation that the decision-making plan has a large error from the actual warehouse resource allocation plan and the warehouse resource allocation goes wrong.

[0032] (2) When the intelligent decision-making system designed by the present invention performs warehouse resource allocation, it can track the outflowing warehouse resources through RFID technology to judge whether the warehouse resource transfer is normal, so that the decision-making system can adjust the warehouse resource allocation in real time.

[0033] (3) The intelligent decision-making method designed by the present invention constructs a real intelligent decision-making system, which serves the purpose of making an immediate decision on the allocation of warehouse resources, greatly increases the immediacy of warehouse resource allocation, and can greatly avoid the problem of wrong allocation of warehouse resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0035] Figure 1 Schematic diagram of the system process provided for an embodiment of an intelligent decision-making system and method for warehouse resource allocation according to the present invention.

[0036] Figure 2 Schematic diagram of the process of the information acquisition unit provided for an embodiment of an intelligent decision-making system and method for warehouse resource allocation according to the present invention.

[0037] Figure 3 Schematic diagram of the process of the problem-solving unit provided for an embodiment of an intelligent decision-making system and method for warehouse resource allocation according to the present invention.

[0038] Figure 4 Flowchart of the method provided for an embodiment of an intelligent decision-making system and method for warehouse resource allocation according to the present invention. Detailed implementation manners

[0039] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0040] As Figures 1-4 shown, an intelligent decision-making system for warehouse resource allocation provided by an embodiment of the present invention includes an information acquisition unit, an information processing unit, a model unit, a problem-solving unit, a feedback unit, a tracking unit, a security unit, and an optimization unit. There is a communication connection between the output end of the information acquisition unit and the input end of the information processing unit, a communication connection between the output end of the information processing unit and the input end of the model unit, a communication connection between the output end of the model unit and the input end of the problem-solving unit, and a communication connection between the output end of the problem-solving unit and the input end of the feedback unit.

[0041] The information acquisition unit is used to acquire warehouse resource allocation data. The information acquisition unit is connected to the warehouse management system through a network port. The warehouse resource allocation data acquired by the information acquisition unit includes the total quantity of warehouse resources within a production cycle, the allocation quantity of warehouse resources within a production cycle, and the guaranteed quantity of warehouse resources within a production cycle.

[0042] The model unit is used to analyze and calculate the data processed by the information processing unit. The model unit is divided into a calculation module and a prediction module. The calculation module is constructed based on the warehouse resource supply and demand formula, and the supply and demand formula is as follows:

[0043]

[0044] Among them, S i (i = 1, 2, 3... n) is the supply and demand ratio of the i-th type of warehouse resources within a production cycle, is the total ration of the i-th type of warehouse resources within a production cycle, M i (i = 1, 2, 3... n) is the total quantity of the i-th type of warehouse resources within a production cycle, There is no need to replenish the quantity of warehouse resources, when, it is necessary to replenish the quantity of warehouse resources, is the maximum supply-demand ratio of the guaranteed material ration of the i-th type of warehouse resources within a production cycle,

[0045] The prediction module is constructed through the warehouse resource ration speed formula, and the warehouse resource ration rate formula is as follows:

[0046]

[0047] Among them, is the average ration of the i-th type of warehouse resources within a production cycle, is the total ration of the i-th type of warehouse resources within a production cycle. If There is no need to additionally ration the quantity of the i-th type of warehouse resources. If It is necessary to additionally ration the quantity of the i-th type of warehouse resources.

[0048] The information processing unit is used to process the data obtained by the information acquisition unit. The information processing unit includes an identification module, a classification and summarization module, and a correlation module. The identification module identifies the warehouse resource ration data obtained by the information acquisition unit according to the category of warehouse resources. The classification and summarization module classifies and summarizes the obtained warehouse resource ration data according to the results identified by the identification module. The correlation module performs correlation analysis and processing on the data summarized by the classification and summarization module according to the requirements of product production, and the specific steps are as follows:

[0049] S1-1. Confirm various warehouse resources required for product production needs;

[0050] S1-2. Re-summarize the data summarized by the classification and summarization module according to the confirmed product production warehouse resources;

[0051] S1-3. Generate a corresponding warehouse resource ration list for the product according to the summarization results.

[0052] The problem-solving unit generates decision-making plans based on the results analyzed by the model unit and verifies the decision-making plans. The problem-solving unit includes an AI module, a detection module, and a screening module. The AI module searches for decision-making plans for previous resource allocations in the warehouse through keyword search technology. The AI module also searches for resource allocation plans on the Internet through keyword search technology. The detection module is used to input the plans searched by the AI module into the model unit for calculation. The screening module selects 3-5 optimal decision-making plans based on the results detected by the detection module.

[0053] The feedback unit is used to transmit the decision-making plans generated by the problem-solving unit to the warehouse management staff. The feedback unit is established through text message push technology. The feedback unit transmits the decision-making plans generated by the problem-solving unit to the warehouse administrator by means of text messages, emails, and WeChat pushes.

[0054] The tracking unit is used to track the materials flowing out of the warehouse. The tracking unit is used to track the transfer process after the warehouse resources are allocated. The tracking unit is established using RFID (Radio Frequency Identification) technology.

[0055] The security unit is used to ensure the security of the decision-making system. The security unit adopts one of 360 network protection and Huorong protection.

[0056] The optimization unit is used to optimize the decision-making system. The optimization unit is established based on deep learning technology. The optimization unit processes the decision-making system in five ways: algorithm optimization, hardware optimization, parallel computing, model optimization, and data processing;

[0057] It should be noted that algorithm optimization improves the model performance by improving the structure and parameters of the algorithm itself; hardware optimization makes full use of hardware resources to improve the training efficiency. Hardware optimization can significantly improve the training speed and performance of deep learning models; parallel computing decomposes the computing tasks and executes them in parallel, thereby improving the training speed. Parallel computing technology can effectively utilize multi-core processors or distributed computing resources to accelerate the training process of deep learning models; model optimization improves the model performance by adding modules, fine-tuning, etc.; data processing improves the model effect by optimizing the data processing process and adjusting parameters.

[0058] An intelligent decision-making method for warehouse resource allocation, as Figure 4 shown, includes the following steps:

[0059] Step S1. Obtain previous warehouse resource allocation data and classify and summarize the obtained data;

[0060] Step S2. Analyze the classified data and construct a warehouse resource supply and demand formula and a warehouse resource allocation speed formula;

[0061] Step S3. Through the analysis of data, a decision-making system is constructed and divided into eight functional areas: an information acquisition unit, an information processing unit, a model unit, a problem-solving unit, a feedback unit, a tracking unit, a security unit, and an optimization unit;

[0062] Step S4. Connect the decision-making system with the warehouse management system, and the decision-making system obtains the warehouse resource data in real time;

[0063] Step S5. The decision-making system analyzes and calculates the obtained warehouse resource data, and automatically generates a decision-making plan according to the calculation results to manage the allocation of warehouse resources.

[0064] Only some exemplary embodiments of the present invention are described above by way of illustration. Undoubtedly, for those of ordinary skill in the art, various different ways can be used to modify the described embodiments without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. An intelligent decision-making system for warehouse resource allocation, comprising an information acquisition unit, an information processing unit, a model unit, a problem solving unit, a feedback unit, a tracking unit, a security unit and an optimization unit, characterized in that: The output end of the information acquisition unit is in communication connection with the input end of the information processing unit, the output end of the information processing unit is in communication connection with the input end of the model unit, the output end of the model unit is in communication connection with the input end of the problem solving unit, and the output end of the problem solving unit is in communication connection with the input end of the feedback unit; The information acquisition unit is used to acquire warehouse resource allocation data, the information processing unit is used to process the data acquired by the information acquisition unit, the model unit is used to analyze and calculate the data processed by the information processing unit, the problem solving unit generates a decision plan based on the results of the model unit analysis, and verifies the decision plan, the feedback unit is used to transmit the decision plan generated by the problem solving unit to the warehouse manager, the tracking unit is used to track the outflow of materials from the warehouse, the security unit is used to ensure the security of the decision system, and the optimization unit is used to optimize the decision system; The model unit is divided into a calculation module and a prediction module. The calculation module is constructed according to the warehouse resource supply and demand formula. The supply and demand formula is as follows: Among them, S i (i=1,2,3……n) is the supply-demand ratio of the i-th type of warehouse resources in a production cycle, is the total allocation of the i-th type of warehouse resources in a production cycle, M i (i=1,2,3……n) is the total quantity of the i-th type of warehouse resources in a production cycle, No need to replenish warehouse resources. When the number of warehouse resources needs to be replenished, is the maximum supply-demand ratio of material allocation guaranteed within a production cycle of the i-th type of warehouse resources, The prediction module is constructed by the warehouse resource allocation speed formula, and the warehouse resource allocation speed formula is as follows: in, is the average allocation of the i-th type of warehouse resources in one production cycle, is the total allocation of the i-th type of warehouse resources in a production cycle. If the allocation quantity of the i-th type of warehouse resources on the previous day is ≤ No additional allocation of the i-th type of warehouse resources is required. If the i-th type of warehouse resources allocated the previous day > The number of additional warehouse resources of the i-th category needs to be allocated.

2. The intelligent decision-making system for warehouse resource allocation according to claim 1, characterized in that: The information acquisition unit is connected to the warehouse management system through a network port. The warehouse resource allocation data acquired by the information acquisition unit includes the total quantity of warehouse resources in one production cycle, the allocation quantity of warehouse resources in one production cycle, and the minimum quantity of warehouse resources in one production cycle.

3. The intelligent decision-making system for warehouse resource allocation according to claim 1 is characterized in that: The information processing unit includes an identification module, a classification and summarization module and a correlation module. The identification module identifies the warehouse resource allocation data acquired by the information acquisition unit according to the category of the warehouse resources.

4. The intelligent decision-making system for warehouse resource allocation according to claim 3 is characterized in that: The classification and summarization module classifies and summarizes the warehouse resource allocation data obtained through the results of the identification module, and the correlation module performs correlation analysis on the data summarized by the classification and summarization module according to the needs of product production, and the specific steps are as follows: S1-1. Confirm the various warehouse resources required for product production; S1-2. Secondary summary of the data summarized by the classification and induction module based on the confirmed product production warehouse resources; S1-3. Generate a warehouse resource allocation list corresponding to the product based on the summary results.

5. The intelligent decision-making system for warehouse resource allocation according to claim 1 is characterized in that: The problem solving unit includes an AI module, a detection module and a screening module. The AI ​​module searches for previous resource allocation decision plans of the warehouse through keyword search technology. The AI ​​module also searches for resource allocation plans on the Internet through keyword search technology.

6. The intelligent decision-making system for warehouse resource allocation according to claim 5, characterized in that: The detection module is used to input the solutions searched by the AI ​​module into the model unit for calculation, and the screening module screens out 3-5 optimal decision-making solutions through the results of the detection module.

7. The intelligent decision-making system for warehouse resource allocation according to claim 1 is characterized in that: The feedback unit is established through text message push technology, and the feedback unit transmits the decision-making solution generated by the problem-solving unit to the warehouse manager through SMS, email, and WeChat push.

8. The intelligent decision-making system for warehouse resource allocation according to claim 1, characterized in that: The tracking unit is used to track the circulation process after the warehouse resources are allocated. The tracking unit is established using RFID (radio frequency identification) technology, and the security unit adopts one of 360 network protection and Huorong protection.

9. The intelligent decision-making system for warehouse resource allocation according to claim 1, characterized in that: The optimization unit is established based on deep learning technology. The optimization unit processes the decision-making system through five methods: algorithm optimization, hardware optimization, parallel computing, model optimization, and data processing.

10. An intelligent decision-making method for warehouse resource allocation, using an intelligent decision-making system for warehouse resource allocation according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step S1. Obtaining previous warehouse resource allocation data, and classifying and summarizing the acquired data; Step S2. Analyze the classified data and construct warehouse resource supply and demand formula and warehouse resource allocation speed formula; Step S3. Build a decision-making system by analyzing the data, and divide the decision-making system into eight functional areas: information acquisition unit, information processing unit, model unit, problem solving unit, feedback unit, tracking unit, security unit, and optimization unit; Step S4. Connect the decision-making system with the warehouse management system, and the decision-making system obtains warehouse resource data in real time; Step S5. The decision system analyzes and calculates the acquired warehouse resource data, and automatically generates a decision plan based on the calculation results to manage the allocation of warehouse resources.

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