Material storage position determination method and device, equipment and storage medium
By analyzing historical data and user needs, combining intelligent prediction models and first-in-first-out principle, we determine the optimal storage location of materials, solve the problem of inefficient material storage, and achieve more efficient material management and reduce inventory losses.
Patent Information
- Application Number
- CN202411423870.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-12
- Publication Date
- 2025-01-10
AI Technical Summary
The existing technology is inefficient in material storage, which can easily lead to backlog or shortage of materials, cannot effectively follow the first-in-first-out principle, and it is difficult to achieve the optimal storage cargo space allocation.
By determining the upper and lower limits of ideal inventory based on the historical usage data and user needs of candidate materials in the target library, using intelligent prediction models to predict future usage quantities, determining the candidate storage location based on the first-in-first-out principle, and finally determining the target storage location.
It improves the efficiency of material allocation, reduces material backlog and expired waste, reduces inventory loss and management costs, and enhances the ability to respond to emergencies and market changes.
Smart Images
Figure CN119294972A_ABST
Abstract
Description
Technical Field
[0001] The embodiments of the present application relate to the field of warehousing technology, in particular to the field of intelligent vertical warehouse technology, and specifically to a method, device, equipment and storage medium for determining a material storage location. Background Art
[0002] In the operation of power companies, material management is crucial. The application of intelligent vertical warehouses improves the efficiency and management level of material storage.
[0003] The current storage methods are inefficient, prone to backlogs or shortages, and unable to effectively follow the first-in-first-out principle. How to achieve the best storage space allocation for materials in the vertical warehouse to meet the material quota and the first-in-first-out principle and make full use of historical material collection data and the vertical warehouse layout is still a technical problem to be solved. Summary of the invention
[0004] The present application provides a material storage location determination method, device, equipment and storage medium to improve the efficiency of material allocation, reduce material backlog and expiration waste, and reduce inventory loss and management costs.
[0005] According to one aspect of the present application, a method for determining a material storage location is provided, the method comprising:
[0006] Determine the ideal upper and lower limits of the inventory of the candidate materials based on the historical usage data of the candidate materials in the target library and the user needs of the user;
[0007] Based on the intelligent forecasting model, according to the ideal inventory upper and lower limits and the historical usage data, the usage demand of the candidate materials is predicted to obtain the future usage quantity of the candidate materials;
[0008] Based on the first-in-first-out principle, according to the historical usage data and the current inventory data of the candidate materials, determining the candidate storage location of the candidate materials in the target vertical warehouse;
[0009] According to the historical usage data, the future usage quantity and the current inventory data, a target storage location of the candidate material in the target warehouse is determined from the candidate storage locations.
[0010] According to another aspect of the present application, a material storage location determination device is provided, the device comprising:
[0011] An inventory determination module is used to determine the ideal upper and lower limits of the inventory of the candidate materials according to the historical usage data of the candidate materials in the target library and the user needs of the user;
[0012] A quantity forecasting module, for forecasting the usage demand of the candidate materials based on the intelligent forecasting model, according to the ideal inventory upper and lower limits and the historical usage data, to obtain the future usage quantity of the candidate materials;
[0013] A first location determination module, configured to determine a candidate storage location of the candidate material in the target vertical warehouse based on a first-in-first-out principle according to the historical usage data and the current inventory data of the candidate material;
[0014] The second location determination module is used to determine the target storage location of the candidate material in the target warehouse from the candidate storage locations according to the historical usage data, the future usage quantity and the current inventory data.
[0015] According to another aspect of the present application, an electronic device is provided, the electronic device comprising:
[0016] one or more processors;
[0017] A memory for storing one or more programs;
[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement any one of the material storage location determination methods provided in the embodiments of the present application.
[0019] According to another aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, any one of the material storage location determination methods provided in the embodiments of the present application is implemented.
[0020] This application determines the ideal inventory upper and lower limits of candidate materials according to the historical usage data of candidate materials in the target warehouse and the user needs of the users; based on the intelligent prediction model, the usage demand of candidate materials is predicted according to the ideal inventory upper and lower limits and historical usage data to obtain the future usage quantity of candidate materials; based on the first-in-first-out principle, the candidate storage location of candidate materials in the target warehouse is determined according to the historical usage data and the current inventory data of candidate materials; the target storage location of candidate materials in the target warehouse is determined from the candidate storage locations according to the historical usage data, the future usage quantity and the current inventory data. The above technical scheme can shorten the time and distance of material out of the warehouse and improve the efficiency of material allocation by selecting the optimal storage location for candidate materials to optimize the material storage layout, and strictly follow the first-in-first-out principle, which can effectively reduce material backlog and expiration waste, reduce inventory loss and management costs, and use the intelligent prediction model to accurately predict material demand, make material reserves and allocation plans in advance, and enhance the ability of users to respond to emergencies and market changes. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Figure 1 is a flow chart of a material storage location determination method provided according to Embodiment 1 of the present application;
[0022] Figure 2 is a flow chart of a material storage location determination method provided according to Embodiment 2 of the present application;
[0023] Figure 3 It is a structural schematic diagram of a material storage location determination device provided according to Embodiment 3 of the present application;
[0024] Figure 4 It is a structural schematic diagram of an electronic device that implements the material storage location determination method of an embodiment of the present application. DETAILED DESCRIPTION
[0025] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.
[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0027] In addition, it should be noted that the collection, storage, use, processing, transmission, provision and disclosure of historical usage data, user needs and other related data involved in the technical solution of this application are in compliance with the relevant laws and regulations and do not violate public order and good morals.
[0028] Embodiment 1
[0029] Figure 1This is a flow chart of a material storage location determination method provided in the first embodiment of the present application. This embodiment can be applied to the case of allocating storage locations for materials of power companies in an intelligent vertical warehouse, and can be executed by a material storage location determination device. The material storage location determination device can be implemented in the form of hardware and / or software, and the material storage location determination device can be configured in a computer device, such as a server. Figure 1 As shown, the method includes:
[0030] S110. Determine the ideal upper and lower limits of the inventory of the candidate materials based on the historical usage data of the candidate materials in the target library and the user needs of the user.
[0031] Among them, the target warehouse refers to an intelligent warehouse that combines automation equipment and information technology to realize automatic storage and management of goods, and is an efficient warehousing system. Candidate materials refer to materials that may be included in the target warehouse after analysis and screening in inventory management; the candidate materials in the embodiment of the present application may be power reserve materials. Historical usage data refers to statistical information on the actual use and consumption of a certain material or product recorded within a certain time range, which may include information such as the type of material, the time of receipt, the quantity of receipt, and the receipt department; these data can reflect the demand trend, frequency of use, and impact on inventory management of materials. User demand refers to the user's demand for the use of materials and warehouse storage, which may be the production plan or maintenance demand of the power company. The ideal inventory upper and lower limits include the ideal inventory upper limit and the ideal inventory lower limit; the ideal inventory upper limit refers to the maximum inventory value set to meet the expected user demand within a specific period, exceeding this level may lead to inventory backlog, capital occupation and storage cost increase; the ideal inventory lower limit refers to the minimum inventory level set to avoid out-of-stock within a specific period. When the inventory drops to this level, it is necessary to replenish in time to ensure that user demand can be met.
[0032] For example, by analyzing the past usage records of candidate materials in the target warehouse, identifying usage trends, seasonal changes, peak demand and other factors, and combining the production plan and maintenance needs of the power company, the ideal upper and lower inventory limits of the candidate materials are set.
[0033] Furthermore, a certain amount of safety stock can be added based on the ideal inventory lower limit.
[0034] It is understandable that by increasing safety stock, one can prepare for unexpected situations such as unforeseen demand fluctuations or supply chain delays.
[0035] In an optional implementation, based on the historical usage data of candidate materials in the target warehouse and the user needs of the user, before determining the ideal upper and lower limits of the candidate inventory, the historical data on the receipt of power reserve materials is collected and organized, covering information such as the type of materials, receipt time, receipt quantity, and receipt department. The data is cleaned and preprocessed to remove invalid and erroneous data to obtain the historical usage data of the candidate materials.
[0036] S120. Based on the intelligent forecasting model, according to the ideal inventory upper and lower limits and historical usage data, the usage demand of the candidate materials is predicted to obtain the future usage quantity of the candidate materials.
[0037] Among them, intelligent forecasting models refer to the use of advanced technologies such as machine learning and deep learning to analyze historical data and identify potential demand patterns; commonly used models include time series analysis, regression models, and neural networks. Future usage quantity refers to the amount of a material or product that is expected to be consumed or used within a specific time period; this concept is usually calculated based on historical data, market trends, seasonal changes, sales forecasts, and other relevant factors.
[0038] For example, based on the intelligent prediction model, the seasonal demand changes of candidate materials, equipment upgrades, power grid construction planning and other factors are comprehensively considered to predict the future demand for materials and obtain the future usage quantity of the candidate materials.
[0039] It is understandable that with the help of intelligent forecasting models, accurate forecasts of material needs can be made, material reserves and allocation plans can be made in advance, and the ability of users to respond to emergencies and market changes can be enhanced.
[0040] S130. Based on the first-in-first-out principle, according to the historical usage data and the current inventory data of the candidate materials, determine the candidate storage location of the candidate materials in the target vertical warehouse.
[0041] Among them, the first-in, first-out principle is a method of inventory management and accounting, which means that the earliest materials or goods in the warehouse should be the first to be out of the warehouse or sold; the core concept of this principle is to ensure that the materials in the inventory are processed in the order of their entry time to reduce the risk of expiration, loss and obsolescence. Current inventory data refers to the data related to the assessment of the current inventory level and the specific situation of the materials, which can include the current inventory of candidate materials, importance scores, etc. Candidate storage locations refer to the possible storage areas preset for specific materials or goods in inventory management; these locations are analyzed and evaluated to ensure that they can meet the storage needs and access efficiency of materials.
[0042] Exemplarily, based on the first-in-first-out principle, the candidate materials that are about to be shipped out are preferentially allocated to the storage locations close to the shipping port, while ensuring that the storage locations of the newly-stocked candidate materials comply with the first-in-first-out order.
[0043] It is understandable that strictly following the first-in, first-out principle can effectively reduce material backlogs and expiration waste, and reduce inventory losses and management costs.
[0044] S140: Determine a target storage location of the candidate material in the target vertical warehouse from the candidate storage locations based on the historical usage data, future usage quantity, and current inventory data.
[0045] The target storage location refers to the optimal storage location ultimately determined for archiving candidate materials.
[0046] It should be noted that the target storage location may be adjusted based on inventory changes, material usage or warehouse layout to adapt to changing needs.
[0047] In an optional implementation, before determining the target storage location for the candidate materials, a three-dimensional model of the target warehouse can be constructed according to the warehouse layout of the target warehouse; based on the three-dimensional model of the warehouse, the real-time status of the candidate materials in the target warehouse can be displayed.
[0048] Among them, the three-dimensional model of the vertical warehouse refers to a three-dimensional visualization model constructed based on the layout information of the target vertical warehouse in warehouse management; this model is used to comprehensively display the structure, storage location and material status of the vertical warehouse.
[0049] It can be understood that the three-dimensional model of the vertical warehouse can intuitively display the overall layout of the vertical warehouse, including shelves, passages, entrances and exits, etc., so that managers can have a clearer understanding of the utilization of warehouse space; by integrating real-time data, the three-dimensional model of the vertical warehouse can display the current status of candidate materials, including inventory quantity, storage location, entry and exit records, etc., to help managers make timely decisions; the three-dimensional model of the vertical warehouse not only provides visual information, but can also be used to analyze and optimize the warehouse layout, improve the efficiency of goods storage and retrieval, and reduce operating costs; the model can be dynamically updated according to real-time data. When materials enter and exit and inventory changes, the model will automatically reflect these changes, thereby maintaining the accuracy and timeliness of the information.
[0050] The embodiment of the present application determines the ideal inventory upper and lower limits of candidate materials according to the historical usage data of candidate materials in the target warehouse and the user needs of the user; based on the intelligent prediction model, the usage demand of candidate materials is predicted according to the ideal inventory upper and lower limits and historical usage data to obtain the future usage quantity of candidate materials; based on the first-in-first-out principle, the candidate storage location of the candidate materials in the target warehouse is determined according to the historical usage data and the current inventory data of the candidate materials; the target storage location of the candidate materials in the target warehouse is determined from the candidate storage locations according to the historical usage data, the future usage quantity and the current inventory data. The above technical scheme can shorten the time and distance of material out of the warehouse and improve the efficiency of material allocation by selecting the optimal storage location for the candidate materials to optimize the material storage layout, and strictly follow the first-in-first-out principle, which can effectively reduce material backlog and expiration waste, reduce inventory loss and management costs, and use the intelligent prediction model to accurately predict material demand, make material reserves and allocation plans in advance, and enhance the ability of users to respond to emergencies and market changes.
[0051] Embodiment 2
[0052] Figure 2 This is a flow chart of a material storage location determination method provided in accordance with Example 2 of the present application. Based on the technical solutions of the above-mentioned embodiments, this embodiment refines "determining the target storage location of the candidate material in the target warehouse from the candidate storage locations based on historical usage data, future usage quantity and current inventory data" into "determining the candidate distance between the candidate storage location and the exit of the target warehouse; determining the target storage location of the candidate material in the target warehouse from the candidate storage locations based on historical usage data, future usage quantity, current inventory data and candidate distance". It should be noted that for the parts not described in detail in the embodiments of the present application, please refer to the relevant statements of other embodiments. Figure 2 As shown, the method includes:
[0053] S210. Determine the ideal upper and lower limits of the inventory of the candidate materials based on the historical usage data of the candidate materials in the target library and the user needs of the user.
[0054] S220. Based on the intelligent prediction model, according to the ideal inventory upper and lower limits and historical usage data, the usage demand of the candidate materials is predicted to obtain the future usage quantity of the candidate materials.
[0055] S230. Based on the first-in-first-out principle, according to the historical usage data and the current inventory data of the candidate materials, determine the candidate storage location of the candidate materials in the target vertical warehouse.
[0056] Optionally, based on the first-in-first-out principle, the order of candidate materials being dispatched is determined according to historical usage data and current inventory data of the candidate materials; based on the dispatch order, the storage locations to be used that are close to the dispatch port in the target warehouse are sequentially determined as candidate storage locations for the candidate materials.
[0057] Among them, the order of outbound delivery refers to the priority of materials outbound from the warehouse in material management based on the first-in-first-out (FIFO) principle, combined with historical usage data and current inventory data; this process ensures that the earliest materials in the warehouse (i.e. the oldest materials) are taken out first, thereby reducing the risk of expiration, loss or obsolescence. The storage location to be used refers to a specific area reserved in warehouse or inventory management for materials that are about to be shipped out or to be processed; these locations are usually used to store materials that are about to be taken out, ensuring that they can be quickly taken out when needed.
[0058] S240: Determine a candidate distance between the candidate storage location and the exit of the target vertical warehouse.
[0059] Among them, candidate distance refers to the physical distance between a specific candidate storage location and the outbound port of the target warehouse in warehouse management.
[0060] S250: Determine a target storage location of the candidate material in the target vertical warehouse from the candidate storage locations according to the historical usage data, the future usage quantity, the current inventory data and the candidate distance.
[0061] In the embodiment of the present application, the historical usage data includes the frequency of material collection, the quantity of material collection and the time of material entry into the warehouse; the current inventory data includes the material inventory and the material importance score.
[0062] Optionally, the time difference between the material entry time and the current time is calculated to obtain the entry time interval of the candidate material, and the ratio of the material collection quantity and the material inventory is calculated to obtain the inventory ratio of the candidate material; according to the material collection frequency, inventory ratio, candidate distance, entry time interval, future usage quantity and material importance score, the target storage location of the candidate material in the target warehouse is determined from the candidate storage locations.
[0063] Among them, the warehousing time interval refers to the difference between the warehousing time of the materials and the current time. This indicator helps evaluate the freshness and circulation speed of the materials. The inventory ratio refers to the ratio of the number of materials issued to the current inventory, in order to understand the use of materials and inventory adequacy; a higher inventory ratio may mean that the storage location of materials needs to be adjusted to avoid excessive backlogs. The material issuance frequency refers to the frequency of material issuance, to understand which materials are frequently withdrawn in order to optimize their storage location; high-frequency materials should be close to the exit to reduce the withdrawal time. The material importance score refers to the importance level of the materials, which can be divided according to the criticality of the materials in the production operation of the power company.
[0064] Furthermore, the target storage location can be determined by weighted summing up the material collection frequency, inventory ratio, candidate distance, warehousing time interval, future usage quantity and material importance score to obtain the priority score of the candidate storage location; sorting the priority scores, and determining the candidate storage location corresponding to the top priority score as the target storage location of the candidate material in the target warehouse.
[0065] Among them, priority scoring refers to calculating the relative importance of candidate storage locations by weighted summation of multiple evaluation indicators in warehouse management, thereby helping decision makers choose the storage location that best suits specific materials.
[0066] Exemplarily, the priority score may be determined by the following formula:
[0067]
[0068] Among them, Score refers to the priority score. F refers to the frequency of material collection. Q refers to the number of materials collected. S refers to the material inventory. D refers to the candidate distance. T refers to the time interval between warehousing. P refers to the number of future uses. C refers to the importance score. w1, w2, w3, w4, w5 and w6 are weight coefficients, which are artificially set through a large number of experiments and based on actual conditions or experience values.
[0069] It can be understood that through the above algorithms and formulas, the best storage location can be determined comprehensively and accurately for each type of material, thereby improving the space utilization rate and material management efficiency of the intelligent vertical warehouse, reducing inventory costs, and ensuring the timeliness and accuracy of the power company's material supply.
[0070] The embodiment of the present application determines the ideal inventory upper and lower limits of candidate materials according to the historical usage data of candidate materials in the target warehouse and the user needs of the user; based on the intelligent prediction model, the use demand of candidate materials is predicted according to the ideal inventory upper and lower limits and historical usage data to obtain the future usage quantity of candidate materials; based on the first-in-first-out principle, the candidate storage position of the candidate materials in the target warehouse is determined according to the historical usage data and the current inventory data of the candidate materials; the candidate distance between the candidate storage position and the exit of the target warehouse is determined; according to the historical usage data, the future usage quantity, the current inventory data and the candidate distance, the target storage position of the candidate materials in the target warehouse is determined from the candidate storage position. The above technical scheme can shorten the time and distance of material outbound delivery and improve the efficiency of material allocation by selecting the optimal storage position for the candidate materials to optimize the material storage layout, and strictly follow the first-in-first-out principle, which can effectively reduce material backlog and expiration waste, reduce inventory loss and management costs, and with the help of the intelligent prediction model, accurately predict material demand, make material reserves and allocation plans in advance, and enhance the ability of users to respond to emergencies and market changes.
[0071] Embodiment 3
[0072] Figure 3 This is a schematic diagram of a material storage location determination device provided in Example 3 of the present application, which can be applied to the case where storage locations are allocated for materials in an intelligent vertical warehouse. The material storage location determination device can be implemented in the form of hardware and / or software, and the material storage location determination device can be configured in a computer device, such as a server. Figure 3 As shown, the device comprises:
[0073] The inventory determination module 310 is used to determine the ideal inventory upper and lower limits of the candidate materials according to the historical usage data of the candidate materials in the target library and the user needs of the user;
[0074] The quantity forecasting module 320 is used to forecast the usage demand of the candidate materials based on the intelligent forecasting model, according to the ideal inventory upper and lower limits and historical usage data, and obtain the future usage quantity of the candidate materials;
[0075] A first location determination module 330 is used to determine a candidate storage location of the candidate material in the target vertical warehouse based on the first-in-first-out principle according to the historical usage data and the current inventory data of the candidate material;
[0076] The second location determination module 340 is used to determine the target storage location of the candidate material in the target vertical warehouse from the candidate storage locations according to the historical usage data, the future usage quantity and the current inventory data.
[0077] The embodiment of the present application determines the ideal inventory upper and lower limits of candidate materials according to the historical usage data of candidate materials in the target warehouse and the user needs of the user; based on the intelligent prediction model, the usage demand of candidate materials is predicted according to the ideal inventory upper and lower limits and historical usage data to obtain the future usage quantity of candidate materials; based on the first-in-first-out principle, the candidate storage location of the candidate materials in the target warehouse is determined according to the historical usage data and the current inventory data of the candidate materials; the target storage location of the candidate materials in the target warehouse is determined from the candidate storage locations according to the historical usage data, the future usage quantity and the current inventory data. The above technical scheme can shorten the time and distance of material out of the warehouse and improve the efficiency of material allocation by selecting the optimal storage location for the candidate materials to optimize the material storage layout, and strictly follow the first-in-first-out principle, which can effectively reduce material backlog and expiration waste, reduce inventory loss and management costs, and use the intelligent prediction model to accurately predict material demand, make material reserves and allocation plans in advance, and enhance the ability of users to respond to emergencies and market changes.
[0078] Optionally, the second location determination module 340 includes:
[0079] A distance determination unit, used to determine a candidate distance between a candidate storage location and a storage exit of a target vertical warehouse;
[0080] The location determination unit is used to determine the target storage location of the candidate material in the target vertical warehouse from the candidate storage locations according to the historical usage data, the future usage quantity, the current inventory data and the candidate distance.
[0081] Optionally, the historical usage data includes material requisition frequency, material requisition quantity and material storage time; the current inventory data includes material inventory and material importance score; accordingly, the location determination unit includes:
[0082] The data calculation subunit is used to calculate the time difference between the material storage time and the current time to obtain the storage time interval of the candidate materials, and to calculate the ratio of the material requisition quantity and the material inventory to obtain the inventory ratio of the candidate materials;
[0083] The location determination subunit is used to determine the target storage location of the candidate material in the target vertical warehouse from the candidate storage locations according to the material collection frequency, inventory ratio, candidate distance, storage time interval, future usage quantity and material importance score.
[0084] Optionally, the position determination subunit is specifically used for:
[0085] The priority score of the candidate storage location is obtained by taking a weighted sum of the material requisition frequency, inventory ratio, candidate distance, storage time interval, future usage quantity and material importance score;
[0086] The priority scores are sorted, and the candidate storage location corresponding to the highest priority score is determined as the target storage location of the candidate material in the target warehouse.
[0087] Optionally, the first position determination module 330 is specifically configured to:
[0088] Based on the first-in-first-out principle, the order of candidate materials leaving the warehouse is determined according to historical usage data and current inventory data of candidate materials;
[0089] Based on the outbound order, the storage locations to be used that are close to the outbound port in the target warehouse are sequentially determined as candidate storage locations for the candidate materials.
[0090] Optionally, the device further comprises a model building module; the model building module is used to:
[0091] According to the warehouse layout of the target warehouse, a three-dimensional model of the target warehouse is constructed;
[0092] Based on the three-dimensional model of the warehouse, the real-time status of candidate materials in the target warehouse is displayed.
[0093] The material storage location determination device provided in the embodiments of the present application can execute the material storage location determination method provided in any embodiment of the present application, and has the corresponding functional modules and beneficial effects for executing each material storage location determination method.
[0094] Embodiment 4
[0095] Figure 4 4 is a schematic diagram of the structure of an electronic device 410 that implements the material storage location determination method of an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.
[0096] like Figure 4As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411 in communication, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. In RAM413, various programs and data required for the operation of the electronic device 410 can also be stored. The processor 411, ROM412 and RAM413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.
[0097] Multiple components in the electronic device 410 are connected to the I / O interface 415, including: an input unit 416, such as a keyboard, a mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a disk, an optical disk, etc.; and a communication unit 419, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 419 allows the electronic device 410 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.
[0098] The processor 411 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 411 executes the various methods and processes described above, such as a material storage location determination method.
[0099] In some embodiments, the material storage location determination method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the material storage location determination method described above may be performed. Alternatively, in other embodiments, the processor 411 may be configured as the material storage location determination method in any other appropriate manner (e.g., by means of firmware).
[0100] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0101] The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable material storage location determination device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0102] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0103] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).
[0104] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.
[0105] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.
[0106] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.
[0107] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.
Claims
1. A method for determining a material storage location, characterized in that: include: Determine the ideal upper and lower limits of the inventory of the candidate materials based on the historical usage data of the candidate materials in the target library and the user needs of the user; Based on the intelligent forecasting model, according to the ideal inventory upper and lower limits and the historical usage data, the usage demand of the candidate materials is predicted to obtain the future usage quantity of the candidate materials; Based on the first-in-first-out principle, according to the historical usage data and the current inventory data of the candidate materials, determining the candidate storage location of the candidate materials in the target vertical warehouse; According to the historical usage data, the future usage quantity and the current inventory data, a target storage location of the candidate material in the target warehouse is determined from the candidate storage locations.
2. The method according to claim 1, characterized in that The step of determining the target storage location of the candidate material in the target warehouse from the candidate storage locations according to the historical usage data, the future usage quantity and the current inventory data includes: Determine a candidate distance between the candidate storage location and the exit of the target vertical warehouse; According to the historical usage data, the future usage quantity, the current inventory data and the candidate distance, a target storage location of the candidate material in the target vertical warehouse is determined from the candidate storage locations.
3. The method according to claim 2, characterized in that The historical usage data includes material requisition frequency, material requisition quantity and material storage time; the current inventory data includes material inventory and material importance score; accordingly, determining the target storage location of the candidate material in the target vertical warehouse from the candidate storage locations according to the historical usage data, the future usage quantity, the current inventory data and the candidate distance includes: Calculate the time difference between the material entry time and the current time to obtain the entry time interval of the candidate material, and calculate the ratio of the material requisition quantity and the material inventory to obtain the inventory ratio of the candidate material; According to the material collection frequency, the inventory ratio, the candidate distance, the warehousing time interval, the future usage quantity and the material importance score, the target storage location of the candidate material in the target vertical warehouse is determined from the candidate storage locations.
4. The method according to claim 3, characterized in that Determining a target storage location of the candidate material in the target vertical warehouse from the candidate storage locations according to the material requisition frequency, the inventory ratio, the candidate distance, the warehousing time interval, the future usage quantity and the material importance score, includes: The priority score of the candidate storage location is obtained by performing a weighted summation on the material requisition frequency, the inventory ratio, the candidate distance, the warehousing time interval, the future usage quantity and the material importance score; The priority scores are sorted, and the candidate storage location corresponding to the highest priority score is determined as the target storage location of the candidate material in the target warehouse.
5. The method according to claim 1, characterized in that The step of determining the candidate storage location of the candidate material in the target warehouse based on the first-in-first-out principle and according to the historical usage data and the current inventory data of the candidate material includes: Based on the first-in-first-out principle, according to the historical usage data and the current inventory data of the candidate materials, determine the order in which the candidate materials are released from storage; Based on the outbound order, the storage locations to be used that are close to the outbound port in the target vertical warehouse are determined in order as candidate storage locations for the candidate materials.
6. The method according to claim 1, characterized in that The method further comprises: According to the vertical warehouse layout of the target vertical warehouse, construct a vertical warehouse three-dimensional model of the target vertical warehouse; Based on the three-dimensional model of the vertical warehouse, the real-time status of the candidate materials in the target vertical warehouse is displayed.
7. A material storage location determination device, characterized in that: include: An inventory determination module is used to determine the ideal upper and lower limits of the inventory of the candidate materials according to the historical usage data of the candidate materials in the target library and the user needs of the user; A quantity forecasting module, for forecasting the usage demand of the candidate materials based on the intelligent forecasting model, according to the upper and lower limits of the ideal inventory and the historical usage data, to obtain the future usage quantity of the candidate materials; A first location determination module, configured to determine a candidate storage location of the candidate material in the target vertical warehouse based on a first-in-first-out principle and according to the historical usage data and the current inventory data of the candidate material; The second location determination module is used to determine the target storage location of the candidate material in the target warehouse from the candidate storage locations according to the historical usage data, the future usage quantity and the current inventory data.
8. An electronic device, characterized in that: include: one or more processors; A memory for storing 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 material storage location determination method as described in any one of claims 1-6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the material storage location determination method as described in any one of claims 1 to 6 is implemented.
10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for determining a material storage location according to any one of claims 1 to 6 is implemented.