Electric power material allocation flexible recommendation method and device, storage medium and equipment

Abstract

The invention discloses an electric power material allocation flexible recommendation method and device, a storage medium and equipment, and relates to the technical field of electric power material supply chain management, and the method comprises the steps: obtaining material basic information and allocation configuration information of a target warehouse; when the materials are warehoused, based on the material basic information, to-be-warehoused material information and the goods allocation configuration information, carrying out goods allocation screening by adopting a preset warehousing rule corresponding to the warehouse type of the target warehouse to obtain a first target goods allocation corresponding to the to-be-warehoused goods; and when the goods and materials are delivered, based on the basic information of the goods and materials, the information of the to-be-delivered goods and the goods allocation configuration information, carrying out goods allocation screening by adopting a preset delivery rule corresponding to the warehouse type of the target warehouse, and obtaining a second target goods allocation corresponding to the to-be-delivered goods. According to the method, automatic and flexible goods allocation recommendation can be realized, and the labor cost and the storage cost are saved.

Description

Technical Field

[0001] The present invention relates to the technical field of power material supply chain management, and particularly to a flexible recommendation method, device, storage medium and equipment for power material storage locations. Background Art

[0002] Modern power material supply chain management faces increasing challenges in supply timeliness and complexity, especially in the storage and distribution of power equipment and materials. The traditional power material warehousing mode mainly relies on the subjective decisions of warehouse keepers and judgment based on operation experience, and it is difficult to accurately and efficiently cope with the current situation of high frequency of power material inbound and outbound, large fluctuations in demand affected by factors such as seasons and centralized start-up of distribution network engineering projects, and a large variety of material demand models. In this case, problems such as unreasonable allocation of warehousing resources, low operation efficiency, and insufficient utilization rate of warehouse capacity frequently occur, which not only directly increases the warehousing cost, but may further affect the reliability of power supply.

[0003] Especially considering the particularity of power materials, such as large equipment and materials like distribution transformers, 10kV outdoor switch cabinets, power cables, and steel core aluminum stranded wires, their volumes, weights, handling and storage requirements are different, which further exacerbates the complexity of power material supply chain management. For example, for tray rack materials, due to different tray rack diameters (heights), it is necessary to consider the optimal utilization of warehouse capacity during storage to avoid fragmented warehouse capacity resulting in excessive occupied storage space. At the same time, if materials with frequent inbound and outbound are too concentrated in the same area, it will lead to overcrowding in the loading and unloading area of the flat warehouse and the problem that the shuttle car in the stereoscopic warehouse stops in the main lane waiting for picking up goods, and the overall operation fluency cannot be guaranteed. Existing warehouse management systems often lack effective data analysis and intelligent decision-making support, and have limited processing capabilities for the inbound and outbound rules, demand forecasting, and optimal use of storage locations of power materials, and cannot flexibly and dynamically adapt to the fluctuations of power material demands and the changes in business forms. Summary of the Invention

[0004] In view of this, the present invention provides a flexible recommendation method, device, storage medium and electronic equipment for power material storage locations, mainly aiming to solve problems such as low efficiency of manual selection of storage locations for current power material inbound and outbound.

[0005] To solve the above problems, the present application provides a flexible recommendation method for power material storage locations, including:

[0006] Obtain the basic information of materials and the storage location configuration information of the target warehouse;

[0007] When materials are warehoused, based on the basic information of the materials, the information of the materials to be warehoused, and the goods location configuration information, a preset warehousing rule corresponding to the warehouse type of the target warehouse is used for goods location screening to obtain a first target goods location corresponding to the goods to be warehoused;

[0008] When materials are out of the warehouse, based on the basic information of the materials, the information of the materials to be out of the warehouse, and the goods location configuration information, a preset outbound rule corresponding to the warehouse type of the target warehouse is used for goods location screening to obtain a second target goods location corresponding to the goods to be out of the warehouse.

[0009] Optionally, when materials are warehoused, based on the basic information of the materials, the information of the materials to be warehoused, and the goods location configuration information, a preset warehousing rule corresponding to the warehouse type of the target warehouse is used for goods location screening to obtain a first target goods location corresponding to the goods to be warehoused, which specifically includes:

[0010] When the warehouse type of the target warehouse is a flat warehouse, calculation and processing are performed based on the historical demand data of the goods to be warehoused within a preset period to obtain the first demand frequency and the first demand quantity of the goods to be warehoused;

[0011] Calculation and processing are performed based on the information of the materials to be warehoused and the goods location configuration information to obtain the first coordinate parameter information of the goods of the same model corresponding to the goods to be warehoused and the second coordinate parameter information of the goods of different models corresponding to the goods to be warehoused;

[0012] Based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, a preset first warehousing function, and a preset second warehousing function, a preset genetic algorithm is used to screen the goods to be warehoused to obtain the first target goods location corresponding to the goods to be warehoused.

[0013] Optionally, the step of using a preset genetic algorithm to screen the goods to be warehoused based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, a preset first warehousing function, and a preset second warehousing function to obtain the first target goods location corresponding to the goods to be warehoused specifically includes:

[0014] Based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, a preset first constraint condition, and preset optimization parameters, the population is initialized to obtain the first initial positions of the individuals in the population, and the preset optimization parameters include the number of individuals and the maximum number of iterations;

[0015] Based on each of the first initial positions, the first storage function and the second storage function are respectively used to perform calculation processing to obtain a first parameter value and a second parameter value corresponding to each of the first initial positions;

[0016] Performing calculation processing based on the first parameter value and the second parameter value corresponding to the same first initial position to obtain a first initial index value corresponding to each first initial position;

[0017] Screening the first initial index values ​​to obtain a first optimal initial position, so as to obtain a first initial recommended cargo position corresponding to the cargo to be stored;

[0018] The first position coordinates of each first initial position are updated by a random crossover mutation method, and the cargo location is re-screened based on the updated first position coordinates, and the cycle is iterated until the number of iterations is equal to a preset threshold, and the updated first initial recommended cargo location is determined as the first target cargo location.

[0019] Optionally, when materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage and the storage location configuration information, a preset storage rule corresponding to the warehouse type of the target warehouse is used to perform storage location screening to obtain a first target storage location corresponding to the materials to be put into storage, further comprising:

[0020] When the warehouse type of the target warehouse is a three-dimensional warehouse, a second demand frequency and a second demand quantity of the goods to be stored are obtained by performing calculation and processing based on the historical demand data of the goods to be stored in a preset period of time;

[0021] Calculation is performed based on the information of the materials to be stored and the cargo location configuration information to obtain the material quality and transfer penalty of the materials to be stored allocated to each cargo location;

[0022] Based on the second demand frequency, the second demand quantity, the quality of each material and the penalty for each warehouse transfer, the preset third warehousing function, the preset fourth warehousing function and the preset fifth warehousing function, a preset genetic algorithm is used to screen the storage locations of the goods to be stored, and the first target storage location corresponding to the goods to be stored is obtained.

[0023] Optionally, the using a preset genetic algorithm to screen the cargo locations of the goods to be stored based on the second demand frequency, the second demand quantity, the quality of each material, the warehouse transfer penalty, the preset third storage function, the preset fourth storage function, and the preset fifth storage function to obtain the first target storage location corresponding to the goods to be stored specifically includes:

[0024] Initialize the population based on the second demand frequency, the second demand quantity, the material quality, the warehouse transfer penalty, the preset second constraint condition and the preset optimization parameters to obtain the second initial position of each individual in the population, wherein the preset optimization parameters include the number of individuals and the maximum number of iterations;

[0025] Based on each of the second initial positions, the third storage function, the fourth storage function and the fifth storage function are used to perform calculation processing to obtain a third parameter value, a fourth parameter value and a fifth parameter value corresponding to each of the second initial positions;

[0026] Performing calculation processing based on the third parameter value, the fourth parameter value, and the fifth parameter value corresponding to the same second initial position to obtain a second initial index value corresponding to each second initial position;

[0027] Screening the second initial index values ​​to obtain a second optimal initial position, so as to obtain a second initial recommended cargo position corresponding to the goods to be stored;

[0028] The second position coordinates of each second initial position are updated by a random crossover mutation method, and the cargo location is re-screened based on the updated second position coordinates, and the cycle is iterated until the number of iterations is equal to a preset threshold, and the updated second initial recommended cargo location is determined as the first target cargo location.

[0029] Optionally, when the materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out, and the cargo location configuration information, a preset shipping rule corresponding to the warehouse type of the target warehouse is used to perform cargo location screening to obtain a second target cargo location corresponding to the goods to be shipped out, specifically including:

[0030] When the warehouse type of the target warehouse is a flat warehouse, the population is initialized based on the basic information of the materials, the information of the materials to be shipped out, the cargo space configuration information, the preset third constraint condition and the preset optimization parameter to obtain a third initial position corresponding to each individual in the population;

[0031] Based on the third position coordinates of the third initial position, the first outbound function and the second outbound function are used to perform calculation processing to obtain the first outbound index and the second outbound index;

[0032] Calculate and process the first outbound index and the second outbound index corresponding to the same third initial position to obtain a third initial index value corresponding to the same third initial position;

[0033] Screening the third initial index values ​​to obtain a third optimal initial position, so as to obtain a third initial recommended cargo position corresponding to the cargo to be shipped out;

[0034] The third position coordinates of each of the third initial positions are updated by using a method of random crossover and mutation, and the storage location screening is re-performed based on the updated third position coordinates. The iteration is carried out in a loop until the number of iterations is equal to a preset threshold, and the updated third initial recommended storage location is determined as the second target storage location.

[0035] Optionally, when the materials are out of storage, based on the basic information of the materials, the information of the materials to be out of storage, and the storage location configuration information, a preset out-of-storage rule corresponding to the warehouse type of the target warehouse is used for storage location screening to obtain a second target storage location corresponding to the goods to be out of storage, and further includes:

[0036] When the warehouse type of the target warehouse is a three-dimensional warehouse, based on the basic information of the materials, the information of the materials to be out of storage, the storage location configuration information, a preset fourth constraint condition, and a preset optimization parameter, a population is initialized to obtain a fourth initial position corresponding to each individual in the population;

[0037] Based on the fourth position coordinates of the fourth initial positions, calculations are respectively performed by using a third out-of-storage function, a fourth out-of-storage function, and a fifth out-of-storage function to obtain a third out-of-storage index, a fourth out-of-storage index, and a fifth out-of-storage index;

[0038] Based on the third out-of-storage index, the fourth out-of-storage index, and the fifth out-of-storage index corresponding to the same fourth initial position, calculations are performed to obtain a fourth initial index value corresponding to the same fourth initial position;

[0039] The fourth optimal initial position is obtained by screening each of the fourth initial index values to obtain a fourth initial recommended storage location corresponding to the goods to be out of storage;

[0040] The fourth position coordinates of each of the fourth initial positions are updated by using a method of random crossover and mutation, and the storage location screening is re-performed based on the updated fourth position coordinates. The iteration is carried out in a loop until the number of iterations is equal to a preset threshold, and the updated fourth initial recommended storage location is determined as the second target storage location.

[0041] To solve the above problems, the present application provides a flexible recommendation device for power material storage locations, including:

[0042] An acquisition module, configured to acquire the basic information of the materials and the storage location configuration information of the target warehouse;

[0043] A first screening module, configured to, when the materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage, and the storage location configuration information, use a preset inbound rule corresponding to the warehouse type of the target warehouse for storage location screening to obtain a first target storage location corresponding to the goods to be put into storage;

[0044] A second screening module, configured to, when materials are out of the warehouse, perform location screening based on the basic information of the materials, the information of the materials to be out of the warehouse, and the location configuration information, and adopt a preset out-of-warehouse rule corresponding to the warehouse type of the target warehouse to obtain a second target location corresponding to the goods to be out of the warehouse.

[0045] To solve the above problems, the present application provides a storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned power material location flexible recommendation method are implemented.

[0046] To solve the above problems, the present application provides an electronic device including at least a memory and a processor. A computer program is stored on the memory, and when the processor executes the computer program on the memory, the steps of the above-mentioned power material location flexible recommendation method are implemented.

[0047] Beneficial effects in the present application: The present application obtains the basic information of materials and the location configuration information of the target warehouse; when materials are put into the warehouse, perform location screening based on the basic information of the materials, the information of the materials to be put into the warehouse, and the location configuration information, and adopt a preset in-warehouse rule corresponding to the warehouse type of the target warehouse to obtain a first target location corresponding to the goods to be put into the warehouse; when materials are out of the warehouse, perform location screening based on the basic information of the materials, the information of the materials to be out of the warehouse, and the location configuration information, and adopt a preset out-of-warehouse rule corresponding to the warehouse type of the target warehouse to obtain a second target location corresponding to the goods to be out of the warehouse. The present application automatically allocates locations through algorithms, especially the application of the principles of short-distance location allocation and balanced workload, making the storage and retrieval of materials more efficient, reducing the walking distance and working time of warehouse operators and equipment, improving the speed of material in and out of the warehouse, and avoiding congestion and waiting situations in the loading and unloading area of the flat warehouse and the shuttle vehicle lane of the stereoscopic warehouse, thereby significantly improving the overall efficiency of warehousing operations. And implement the first-in, first-out principle and minimize the storage capacity fragmentation, optimize the selection of out-of-warehouse locations, effectively solve the problems of insufficient storage capacity utilization and inventory stagnation and backlog, enable the storage capacity space of the warehouse to be reasonably and fully utilized, maximize the storage capacity, and at the same time reduce the warehousing cost.

[0048] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the following specifically illustrates the specific embodiments of the present invention. Description of the Drawings

[0049] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the following detailed description of the preferred embodiments. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Also, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0050] Figure 1 Fig. shows a schematic flowchart of a method for flexibly recommending storage locations for electric power materials provided by an embodiment of the present application;

[0051] Figure 2 Fig.

[0050] shows a schematic flowchart of a method for flexibly recommending storage locations for electric power materials provided by another embodiment of the present application;

[0052] Figure 3 Fig. Figure 1 shows a schematic diagram of storage location No. 03402 in an open storage yard provided by an embodiment of the present application;

[0053] Figure 4 Fig. shows a schematic diagram of a rectangular coordinate system of a planar warehouse provided by an embodiment of the present application;

[0054] Figure 5 Fig.

[0051] shows a schematic diagram of penalty for material transfer provided by an embodiment of the present application;

[0055] Figure 6 Fig. Figure 2 shows a structural block diagram of a device for flexibly recommending storage locations for electric power materials provided by another embodiment of the present application. Detailed Embodiments

[0056] Reference is made herein to the various aspects and features of the present application with reference to the drawings.

[0057] It should be understood that various modifications can be made to the embodiments described herein. Therefore, the above description should not be regarded as a limitation, but only as an example of the embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the present application.

[0058] The drawings included in and forming a part of this specification illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0059] These and other features of the present application will become apparent from the following description of the preferred forms of the embodiments given as non - limiting examples with reference to the drawings.

[0060] It should also be understood that, although the present application has been described with reference to some specific examples, those skilled in the art can surely implement many other equivalent forms of the present application.

[0061] When combined with the accompanying drawings, the above and other aspects, features, and advantages of the present application will become more apparent in view of the following detailed description.

[0062] Specific embodiments of the present application will be described hereinafter with reference to the accompanying drawings; however, it should be understood that the embodiments claimed are merely examples of the present application and can be implemented in various ways. Well-known and / or repetitive functions and structures are not described in detail to avoid obscuring the present application with unnecessary or redundant details. Therefore, the specific structural and functional details claimed herein are not intended to be limiting, but are merely used as a basis for the claims and a representative basis for teaching those skilled in the art to use the present application in substantially any suitable detailed structure in a variety of ways.

[0063] This specification may use the phrases "in one embodiment", "in another embodiment", "in yet another embodiment", or "in other embodiments", each of which may refer to one or more of the same or different embodiments according to the present application.

[0064] An embodiment of the present application provides a method for flexible recommendation of storage locations for electric power materials, as Figure 1 shown, including:

[0065] Step S101: Obtain the basic information of materials and the storage location configuration information of the target warehouse;

[0066] In the specific implementation process of this step, the basic information of the materials includes the storage goods information of the target warehouse, and the storage goods information includes the goods model of the storage goods, the demand frequency within a preset period, the demand quantity within a preset period, the coordinate position, orientation, size, packaging type, supply form, palletizing form, applicable storage location type of the storage goods, and the warehousing information, including information such as the material name, model, quantity, contract number, manufacturer, batch number, unit price tax, warehousing date, and asset code; the storage location configuration information includes fixed storage location configuration information, special storage location configuration information, mobile storage location configuration information, the order of storage location use, and the working habits of warehouse keepers, etc.

[0067] Step S102: When materials are warehoused, based on the basic information of the materials, the information of the materials to be warehoused, and the storage location configuration information, use a preset warehousing rule corresponding to the warehouse type of the target warehouse to screen storage locations, and obtain the first target storage location corresponding to the goods to be warehoused;

[0068] In the specific implementation process of this step, when materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage and the storage location configuration information, the first storage function of the "close-range storage location allocation principle" and the second storage function of the "balanced workload principle" are used as optimization targets for the storage of materials in the flat warehouse to make flexible storage location recommendations; considering the storage location information, the operating parameters of automated storage equipment such as shuttles and elevators, the third storage function of the "fast entry and exit principle", the fourth storage function of the "shelf stability principle" and the fifth storage function of the "minimum number of transfers principle" are used as optimization targets for the storage of materials in the three-dimensional warehouse to make flexible storage location recommendations.

[0069] Step S103: When materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the cargo location configuration information, the preset shipping rules corresponding to the warehouse type of the target warehouse are used to screen the cargo locations to obtain a second target cargo location corresponding to the goods to be shipped out.

[0070] In the specific implementation process of this step, when materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the storage location configuration information, for the shipping of flat materials, the first shipping function based on the "first-in-first-out supply principle" and the second shipping function based on the "principle of minimizing storage capacity fragmentation" are adopted as optimization targets to recommend flexible storage locations; for the shipping of materials from a three-dimensional warehouse, based on the basic information of the materials, the information of the materials to be shipped out and the storage location configuration information, the third shipping function based on the "first-in-first-out supply principle", the fourth shipping function based on the "principle of fast in and out of the warehouse" and the fifth shipping function based on the "principle of minimum number of warehouse transfers" are adopted as optimization targets to recommend flexible storage locations.

[0071] This application obtains the basic material information and storage location configuration information of the target warehouse; when materials are warehoused, based on the basic material information, the materials to be warehoused information, and the storage location configuration information, a preset warehousing rule corresponding to the warehouse type of the target warehouse is used to screen storage locations, and the first target storage location corresponding to the goods to be warehoused is obtained; when materials are out of the warehouse, based on the basic material information, the materials to be out of the warehouse information, and the storage location configuration information, a preset out-of-warehouse rule corresponding to the warehouse type of the target warehouse is used to screen storage locations, and the second target storage location corresponding to the goods to be out of the warehouse is obtained. This application automatically allocates storage locations through algorithms. Especially the application of the principles of short-distance storage location allocation and balanced workload, makes the storage and retrieval of materials more efficient, reduces the walking distance and operation time of warehouse operators and equipment, improves the speed of material warehousing and out-of-warehouse, and avoids congestion and waiting situations in the loading and unloading area of the flat warehouse and the shuttle lane of the three-dimensional warehouse, thus significantly improving the overall efficiency of warehousing operations. And the first-in, first-out principle is implemented and the storage capacity fragmentation is minimized, optimizing the selection of out-of-warehouse storage locations, effectively solving the problems of insufficient storage capacity utilization and inventory stagnation and backlog, enabling the storage capacity space of the warehouse to be reasonably and fully utilized, maximizing the storage capacity, and at the same time reducing the warehousing cost.

[0072] Another embodiment of this application provides another method for flexible recommendation of power material storage locations, as Figure 2 shown, including:

[0073] Step S201: Obtain the basic material information and storage location configuration information of the target warehouse;

[0074] In the specific implementation process of this step, the basic material information includes the storage goods information of the target warehouse, and the storage goods information includes the goods model of the storage goods, the demand frequency within a preset period and the demand quantity within a preset period, the coordinate position, orientation, size, packaging type, supply form, palletizing form, applicable storage location type of the storage goods, and the warehousing information, including information such as material name, model, quantity, contract number, manufacturer, batch number, unit price tax, warehousing date, and asset code; the storage location configuration information includes fixed storage location configuration information, special storage location configuration information, flexible storage location configuration information, storage location usage order, and the work habits of warehouse keepers, etc.

[0075] Step S202: When the target warehouse is a flat warehouse, calculate and process based on the historical demand data of the goods to be warehoused within a preset period to obtain the first demand frequency and the first demand quantity of the goods to be warehoused;

[0076] In the specific implementation process of this step, the calculation mathematical formula of the first demand frequency can be shown by the following formula (1):

[0077]

[0078] The mathematical expression of the first required quantity can be shown by the following formula (2):

[0079] Q k = total demand of material of model k in a preset period (2)

[0080] where k is the material model: P k is the demand frequency of material of model k within a preset period; Q k is the total demand of material of model k within a preset period.

[0081] Step S203: Perform calculation and processing based on the to-be-stored material information and the storage location configuration information to obtain the first coordinate parameter information of the goods of the same model corresponding to the to-be-stored goods and the second coordinate parameter information of the goods of different models corresponding to the to-be-stored goods;

[0082] In the specific implementation process of this step, materials with high inbound and outbound frequencies are placed near the entrance and exit of the warehouse (warehouse area). However, if the distance between materials with frequent inbound and outbound is too close, it will cause problems such as tight loading positions for trucks in the flat warehouse site and shuttle cars in the automated storage and retrieval system (AS / RS) waiting for picking goods in the same aisle, resulting in trucks queuing for loading in the flat warehouse and shuttle cars queuing for picking goods in the aisle of the AS / RS. Therefore, when warehousing, consider balancing the distribution of materials in each flat warehouse storage location and the storage area of the AS / RS. Calculate the turnover rate difference between the to-be-stored materials and the in-stock materials in the flat warehouse storage location (storage area of the AS / RS) according to the turnover rate of materials in the flat warehouse storage location (storage area of the AS / RS), and try to store materials with a larger turnover rate difference adjacent to each other. Specifically, determine the first row coordinate l of the target warehouse storing materials of the same model as the material model based on the material model of the to-be-stored material information nk and determine the second row coordinate of the target warehouse storing materials of different models from the material model Perform mean value calculation based on each of the first row coordinates to obtain the first coordinate parameter information Perform mean value calculation based on each of the second row coordinates to obtain the second coordinate parameter information

[0083] Step S204: Use a preset genetic algorithm to screen storage locations for the to-be-stored goods based on the first demand frequency, the first required quantity, the first coordinate parameter information, the second coordinate parameter information, a preset first warehousing function, and a preset second warehousing function to obtain the first target storage location corresponding to the to-be-stored goods;

[0084] In the specific implementation of this step, when the target warehouse is a flat warehouse, materials with high inbound and outbound frequencies have a crucial impact on the operation efficiency of the flat warehouse. Therefore, materials with high inbound and outbound frequencies are stored in storage locations near the warehouse entrance and exit or in the warehouse area that are convenient for loading and unloading. In addition, demand is also one of the reasons for high inbound and outbound frequencies of goods. Storing materials with high demand in storage locations near the warehouse entrance and exit or in the warehouse area that are convenient for loading and unloading can achieve the purpose of improving the operation efficiency of the flat warehouse. Since when the same type of materials are warehoused, materials with the same manufacturer and the same model must be placed in the same column, first, materials of the same model and the same manufacturer are combined into columns, and the number of rows that can be arranged according to the depth of the storage location (i.e., the number that can be placed in one column) is calculated. The quotient of the total number of inbound materials and the number placed in each column is rounded up to obtain the number of inbound columns for this batch of goods. As Figure 3 shows a schematic diagram of storage location No. 03402 in the open storage yard of this application; currently, there are 11 transformers of a certain model from a certain manufacturer. According to the depth of the storage location in Warehouse No. 3, 7 transformers can be stored in each column. At this time, the 11 transformers actually occupy 2 columns of the storage capacity. For low-turnover wire reels (mainly referring to steel-core aluminum stranded wire, aluminum-clad steel stranded wire, 10kV overhead insulated wire, etc.), since they can be mixed and arranged, they can be arranged according to the rules. The wire reels with large diameters are placed inside (the enclosure wall) of the storage location, and the wire reels with small diameters are close to the warehouse area passage (the outside) to form as few columns as possible and reduce the use of storage capacity. For combined materials, they are arranged in the order of "main body to accessories" in accordance with the principle of "classify first and then list" to obtain the number of columns for the arrangement of combined materials. The orientations of combined materials in the storage location are all placed according to the rules preset by the warehouse keeper. Then, calculate the distance of each column from the entrance and exit, and construct a rectangular coordinate system for the flat warehouse to determine the origin coordinates of the rectangular coordinate system and the x-axis and y-axis; as Figure 4 shown, the lower left corner of the flat warehouse can be used as the origin, and the entrance and exit position is (io x , io y ). Since the inbound is in whole columns, the horizontal axis coordinate difference is taken here as the distance of each column of materials from the entrance and exit. The distance l n represents the distance of the nth column of materials from the entrance and exit, and l n =n x -io x . The distance of the nth column where the material model k is located from the exit can be expressed as l nk . The mathematical expression of the preset first inbound function can be shown by the following formula (3):

[0085]

[0086] where K is the number of material models; N is the number of columns of materials arranged in the warehouse area; l nkis the distance of the n columns where the material model k is located from the exit. Materials with high inbound and outbound frequencies are placed close to the entrance and exit of the warehouse (warehouse area). However, if the distances between frequently inbound and outbound materials are too close, it will lead to problems such as a shortage of loading truck positions at the flat warehouse site and shuttle cars in the automated storage and retrieval system (AS / RS) waiting for picking in the same aisle, resulting in trucks queuing for loading at the flat warehouse and shuttle cars queuing for picking in the aisle at the AS / RS. Therefore, when warehousing, consider balancing the distribution of materials in each flat warehouse storage location and in the storage area of the AS / RS. Calculate the turnover rate difference between the currently incoming materials and the in-stock materials in the flat warehouse storage location (storage area of the AS / RS) according to the turnover rate of the materials in the flat warehouse storage location (storage area of the AS / RS). Try to store materials with a larger turnover rate difference adjacent to each other. Based on the principle of balancing the workload, the preset second warehousing function is constructed. The mathematical expression of the preset second warehousing function can be shown by the following formula (4):

[0087]

[0088] where S k represents the material turnover frequency of the material model with the largest turnover rate difference from the current model material. The mathematical expression of the material turnover frequency can be shown by the following formula (5):

[0089] S k = max(P k - P Rk )(5)

[0090] where the mathematical expression of the demand frequency P Rk of the material models other than k in the material category to which the k model material belongs can be shown by the following formula (6):

[0091]

[0092] Specifically, initialize the population based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, the preset first constraint condition, and the preset optimization parameters to obtain the first initial positions of each individual in the population. The preset optimization parameters include the number of individuals M and the maximum number of iterations T. An individual is a set of flexible storage location recommendation solutions for the warehousing task of the goods to be warehoused, that is, a set of feasible solutions. When the goods to be warehoused are one piece of equipment, the position coordinates corresponding to one piece of equipment are obtained. When the goods to be warehoused are multiple pieces of equipment, the position coordinates corresponding to each of the multiple pieces of equipment are obtained. Calculate and process each of the first initial positions respectively using the first warehousing function and the second warehousing function to obtain the first parameter value and the second parameter value corresponding to each of the first initial positions. The first constraint condition includes actual constraint conditions such as the availability of the storage location range, the orientation of the material storage position being consistent with the required placement direction of the storage location, the number of recommended warehousing positions being equal to the total capacity of the storage positions required for the warehousing task in the planar warehouse, and materials of the same manufacturer, the same model, and the same batch number must be placed in the same column. The first preset condition is set according to actual needs. Calculate and process based on the first parameter value and the second parameter value corresponding to the same first initial position to obtain the first initial index value corresponding to each of the first initial positions. The first parameter value and the second parameter value can be subjected to an addition operation to obtain the first initial index value corresponding to each of the first initial positions. Screen each of the first initial index values to obtain the first optimal initial position to obtain the first initial recommended storage location corresponding to the goods to be warehoused. Determine the first initial position corresponding to the smallest first initial index value among each of the first initial index values as the first optimal initial position. The coordinate value corresponding to the first optimal initial position is the optimal recommended coordinate position of the equipment to be warehoused in the current iteration cycle. Use the method of random crossover and mutation to update the first position coordinates of each of the first initial positions, and re-screen the storage locations based on the updated first position coordinates. Iterate in a loop until the number of iterations is equal to the preset threshold, and determine the updated first initial recommended storage location as the first target storage location. Randomly crossover the gene expressions of the coordinate positions of half of the individuals in the population. Specifically, perform pairwise combinations among the M sets of recommendation solutions (M sets of feasible solutions), and randomly exchange the coordinates of each material in the planar warehouse of the 2 recommendation solutions (feasible solutions) in a single combination. Then randomly mutate the gene expressions of the coordinate positions of the individuals in the population. For each material in each of the M sets of recommendation solutions (M sets of feasible solutions), its planar warehouse coordinates randomly change within the limit range of its coordinate system (i.e., the variable range of the x and y axes), and update the coordinate position genes of each individual in the population for the iterative process of the next iteration round. Until the number of iterations is equal to the preset threshold, determine the updated first initial recommended storage location as the first target storage location.The location gene is a set of planar warehouse location coordinates of each incoming material in the flexible storage location recommendation plan for incoming materials in the planar warehouse.

[0093] Step S205: When the warehouse type of the target warehouse is a three-dimensional warehouse, a second demand frequency and a second demand quantity of the goods to be stored are obtained by performing calculations based on the historical demand data of the goods to be stored in a preset period of time;

[0094] In the specific implementation process of this step, when the target warehouse is a three-dimensional warehouse, the historical demand data of the goods to be stored in the preset period is calculated and processed to obtain the second demand frequency and the second demand quantity of the goods to be stored, and the number of demand items of the same type as the goods to be stored in the target warehouse in the preset period and the total number of demand items of the same type as the goods to be stored in the preset period are divided and processed to obtain the second demand frequency p corresponding to the goods to be stored. w ; Determine the total demand for the same type of goods to be stored in the preset period as the second demand quantity Q w , wherein the preset time period can be the first quarter before the current moment or the one month before the current moment, and the preset time period can be set according to actual needs.

[0095] Step S206: Calculate and process the materials to be stored based on the information of the materials to be stored and the storage location configuration information to obtain the material quality and transfer penalty of the materials to be stored allocated to each storage location;

[0096] In the specific implementation process of this step, the storage locations allocated for incoming warehousing should generate as few transfer tasks as possible, which can also greatly improve the efficiency of incoming warehousing. For multi-depth three-dimensional shelves, if the recommended storage location for incoming warehousing is in a deeper location, the materials in all the storage locations on the branch aisles must be transferred before the materials can be placed in the deeper storage locations of the branch aisles. According to the deep location, the number of occupied storage locations at each deep location from the main aisle is calculated as the penalty value for the transfer operation required for the currently allocated incoming warehousing location. For example, Figure 5 As shown in the figure, a material to be stored is to be placed at the fourth deepest position in the branch lane. At this time, there are 3 cargo spaces near the main lane (located at the left end of the figure) that have been occupied by other materials. Then the transfer penalty Aw for the cargo placed at this position is i That’s 3.

[0097] Step S207: Based on the second demand frequency, the second demand quantity, the quality of each material, the penalty for each warehouse transfer, the preset third warehouse entry function, the preset fourth warehouse entry function, and the preset fifth warehouse entry function, a preset genetic algorithm is used to screen the cargo locations of the goods to be warehoused, and the first target cargo location corresponding to the goods to be warehoused is obtained;

[0098] In the specific implementation process of this step, based on the second required frequency, the second required quantity, the material quality, the penalty for inventory transfer, the preset second constraint conditions, and the preset optimization parameters, the population is initialized to obtain the second initial positions of each individual in the population. The preset optimization parameters include the number of individuals and the maximum number of iterations. Based on each of the second initial positions, the third warehousing function, the fourth warehousing function, and the fifth warehousing function are respectively used for calculation and processing to obtain the third parameter value, the fourth parameter value, and the fifth parameter value corresponding to each of the second initial positions. The second constraint conditions include that the number of storage locations for material warehousing should be equal to the number of storage locations matching the quantity of materials in the warehousing task, the recommended target storage location row, column, and tier positions are selected from the rows, columns, and tiers configured in the three-dimensional warehouse, and the target storage location status is empty and available, etc. The mathematical expression of the third warehousing function can be shown by the following formula (7):

[0099]

[0100] Among them, The distance of the i-th storage location allocated for w-type materials from the entrance and exit in the x-axis direction of the three-dimensional warehouse shelf; The distance of the i-th storage location allocated for w-type materials from the entrance and exit in the y-axis direction of the three-dimensional warehouse shelf; The distance of the i-th storage location allocated for w-type materials from the entrance and exit in the z-axis direction of the three-dimensional warehouse shelf; v x , v y The average moving speed of the shuttle car in the x and y directions of the three-dimensional warehouse coordinate axes; v z The average moving speed of the elevator in the z-axis direction of the three-dimensional warehouse coordinate axis; P w Is the second required frequency, Q w Is the second required quantity. The mathematical expression of the fourth warehousing function can be shown by the following formula (8):

[0101]

[0102] Among them, z is the total number of layers of the shelf, k is the total number of rows of the shelf, and n is the total number of columns of the shelf; M iwj Is the material quality stored in the i-th layer, w-th row, and j-th column; H i Represents the height of the i-th layer. The mathematical expression of the fifth warehousing function can be shown by the following formula (9):

[0103]

[0104] Among them, Aw iIt represents the penalty number for the relocation operation that must be performed for the materials of model w placed in the i-th storage location of the branch roadway. Based on the third parameter value, the fourth parameter value, and the fifth parameter value corresponding to the same second initial position, calculation and processing are performed to obtain the second initial index value corresponding to each second initial position; screening processing is performed on each second initial index value to obtain the second optimal initial position, so as to obtain the second initial recommended storage location corresponding to the goods to be warehoused; the second position coordinates of each second initial position are updated by using the method of random crossover and mutation, and storage location screening is re-performed based on the updated second position coordinates, and the loop iteration is performed until the iteration number is equal to the preset threshold, and the updated second initial recommended storage location is determined as the first target storage location.

[0105] Step S208: When the materials are out of the warehouse, based on the basic information of the materials, the information of the materials to be out of the warehouse, and the storage location configuration information, the preset out-of-warehouse rules corresponding to the warehouse type of the target warehouse are used for storage location screening to obtain the second target storage location corresponding to the goods to be out of the warehouse.

[0106] In the specific implementation process of this step, when the warehouse type of the target warehouse is a flat warehouse, for the out-of-warehouse of flat warehouse materials, the "first-in, first-out supply principle" and the "principle of minimizing the generation of storage capacity fragments" are used as the optimization objectives for flexible storage location recommendation. Specifically, based on the basic information of the materials, the information of the materials to be out of the warehouse, the storage location configuration information, the preset third constraint conditions, and the preset optimization parameters, the population is initialized to obtain the third initial position corresponding to each individual in the population; the third constraint conditions can be that the quantity of materials out of the warehouse should be equal to the quantity of materials required for the out-of-warehouse task, the quantity of materials in each storage location is known, the storage time of materials in each storage location is known, the quantity of materials required for the out-of-warehouse task is not more than the total quantity of materials of the same model in the flat warehouse, and the status of materials in the target storage location is in an out-of-warehouse state and other out-of-warehouse constraint conditions. Based on the third position coordinates of the third initial position, the first out-of-warehouse function and the second out-of-warehouse function are respectively used for calculation and processing to obtain the first out-of-warehouse index and the second out-of-warehouse index; the mathematical expression of the first out-of-warehouse function constructed by using the first-in, first-out supply principle can be shown by the following formula (10):

[0107]

[0108] where D today is the current date; is the storage date of the materials in the i-th storage location allocated; when out of the warehouse, try to out of the warehouse in whole batches as much as possible, leaving a whole area (storage capacity) for other materials to be warehoused. Here, the concept of storage capacity fragments is proposed, and this goal also means considering generating smaller storage capacity fragments when the materials are out of the warehouse. The mathematical expression of the second out-of-warehouse function constructed by using the principle of minimizing the generation of storage capacity fragments can be shown by the following formula (11):

[0109]

[0110] where p k represents the fragment size generated after n units of the kth material are out of the warehouse; p k The mathematical expression of can be shown by the following formula (12):

[0111]

[0112] Based on the first outbound index and the second outbound index corresponding to the same third initial position, calculation processing is performed to obtain a third initial index value corresponding to the same third initial position; screening processing is performed on each of the third initial index values to obtain a third optimal initial position, so as to obtain a third initial recommended storage location corresponding to the goods to be out of the warehouse; the third position coordinates of each of the third initial positions are updated by using a random crossover and mutation method, and storage location screening is re-performed based on the updated third position coordinates, and iteration is performed in a loop until the number of iterations is equal to a preset threshold, and the updated third initial recommended storage location is determined as the second target storage location.

[0113] When the warehouse type of the target warehouse is a three-dimensional warehouse, based on the basic material information, the material information to be out of the warehouse, the storage location configuration information, a preset fourth constraint condition, and a preset optimization parameter, a population is initialized to obtain a fourth initial position corresponding to each individual in the population; the fourth constraint condition includes that the quantity of materials out of the warehouse should be equal to the quantity of materials required for the outbound task, the recommended target storage location row, column, and row positions are selected from the rows, columns, and rows configured in the three-dimensional warehouse, and the material status of the target storage location is in an outboundable state and other constraint conditions. For the outbound of materials in a three-dimensional warehouse, the "first-in, first-out supply principle", the "fast inbound and outbound principle", and the "least number of stock transfer principle" are used as optimization objectives for flexible storage location recommendation. Based on the fourth position coordinates of the fourth initial position, calculation processing is respectively performed by using a third outbound function, a fourth outbound function, and a fifth outbound function to obtain a third outbound index, a fourth outbound index, and a fifth outbound index; similar to the flexible storage location recommendation for the outbound of materials in a planar warehouse, the flexible storage location recommendation for the outbound of materials in a three-dimensional warehouse also adopts the first-in, first-out supply principle. The inbound materials are marked in units of natural days, and the batches that are warehoused earlier are given priority to be out of the warehouse. The mathematical expression of the third outbound function constructed by adopting the first-in, first-out supply principle can be shown by the following formula (13):

[0114]

[0115] where D today is the current date; The warehousing date of the materials in the i-th allocated storage location; n is the number of batches. Similar to the flat warehouse, in order to achieve fast in-and-out in the three-dimensional warehouse, materials with high in-and-out frequencies and large demand quantities should be placed as close as possible to the main aisle or the elevator, so as to reduce the picking time of the shuttle car in the three-dimensional warehouse and meet the requirement of fast in-and-out. The mathematical expression of the fourth outbound function constructed by using the above-mentioned fast in-and-out principle can be shown by the following formula (14):

[0116]

[0117] Wherein, The distance of the i-th storage location allocated for w-type materials from the entrance and exit in the x-axis direction of the three-dimensional warehouse shelf; The distance of the i-th storage location allocated for w-type materials from the entrance and exit in the y-axis direction of the three-dimensional warehouse shelf; The distance of the i-th storage location allocated for w-type materials from the entrance and exit in the z-axis direction of the three-dimensional warehouse shelf; v x , v y is the average moving speed of the shuttle car in the x and y directions of the three-dimensional warehouse coordinate axis; v z is the average moving speed of the elevator in the z-axis direction of the three-dimensional warehouse coordinate axis; p w is the demand frequency of material type w. When the preset time period is one quarter, the calculation mathematical formula of p w is shown by the following formula (15):

[0118]

[0119] Q w is the demand quantity of material type w within the preset time period. Similar to the recommendation of flexible storage locations for warehousing materials in the three-dimensional warehouse, the mathematical expression of the fifth outbound function constructed by using the principle of minimizing the number of relocation operations can be shown by the following formula (16):

[0120]

[0121] Wherein, Aw i represents the penalty number for the relocation operation that must be performed when the w-type materials are placed in the i-th storage location in the branch aisle.

[0122] Based on the third outbound index, the fourth outbound index, and the fifth outbound index corresponding to the same fourth initial position, perform calculation processing to obtain the fourth initial index value corresponding to the same fourth initial position; perform screening processing on each of the fourth initial index values to obtain the fourth optimal initial position, so as to obtain the fourth initial recommended storage location corresponding to the goods to be outbound; use the method of random crossover and mutation to update the fourth position coordinates of each of the fourth initial positions, and re-perform storage location screening based on the updated fourth position coordinates, and iterate cyclically until the number of iterations is equal to the preset threshold, then determine the updated fourth initial recommended storage location as the second target storage location.

[0123] The application of the principles of short-distance storage location allocation and balanced workload in this application makes the storage and retrieval of materials more efficient, reduces the walking distance and working time of warehouse workers and equipment, improves the speed of material inbound and outbound, and avoids congestion and waiting situations in the loading and unloading area of the flat warehouse and the shuttle lane of the stereoscopic warehouse, thus significantly improving the overall efficiency of warehousing operations. And by implementing the first-in, first-out principle and minimizing the storage capacity fragmentation, optimizing the selection of outbound storage locations, effectively solving the problems of insufficient storage capacity utilization and inventory stagnation and backlog, enabling the storage capacity space of the warehouse to be reasonably and fully utilized, maximizing the storage capacity, and at the same time reducing the warehousing cost. Through the design of preset constraint conditions and dynamic adjustment of the storage location usage strategy in this application, it is ensured that in the face of actual operation constraints and changes or adjustments in the business form, the storage location recommendation strategy can be flexibly adjusted to maintain the continuity and stability of operations.

[0124] Another embodiment of this application provides a flexible recommendation device for power material storage locations, as Figure 6 shown, including:

[0125] An acquisition module 1, configured to acquire the basic information of materials and the storage location configuration information of the target warehouse;

[0126] A first screening module 2, configured to, when materials are inbound, based on the basic information of the materials, the information of the materials to be inbound, and the storage location configuration information, perform storage location screening using a preset inbound rule corresponding to the warehouse type of the target warehouse to obtain a first target storage location corresponding to the goods to be inbound;

[0127] A second screening module 3, configured to, when materials are outbound, based on the basic information of the materials, the information of the materials to be outbound, and the storage location configuration information, perform storage location screening using a preset outbound rule corresponding to the warehouse type of the target warehouse to obtain a second target storage location corresponding to the goods to be outbound.

[0128] In the specific implementation process, the first screening module 2 is specifically configured to: when the warehouse type of the target warehouse is a flat warehouse, perform calculation processing based on the historical demand data of the goods to be warehoused within a preset time period to obtain the first demand frequency and the first demand quantity of the goods to be warehoused; perform calculation processing based on the information of the goods to be warehoused and the goods location configuration information to obtain the first coordinate parameter information of the goods of the same model corresponding to the goods to be warehoused and the second coordinate parameter information of the goods of different models corresponding to the goods to be warehoused; perform goods location screening on the goods to be warehoused by using a preset genetic algorithm based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, a preset first warehousing function, and a preset second warehousing function to obtain the first target goods location corresponding to the goods to be warehoused.

[0129] In the specific implementation process, the first screening module 2 is further configured to: initialize a population based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, a preset first constraint condition, and a preset optimization parameter to obtain the first initial positions of the individuals in the population, where the preset optimization parameter includes the number of individuals and the maximum number of iterations; perform calculation processing on each of the first initial positions by using the first warehousing function and the second warehousing function respectively to obtain the first parameter value and the second parameter value corresponding to each of the first initial positions; perform calculation processing based on the first parameter value and the second parameter value corresponding to the same first initial position to obtain the first initial index value corresponding to each of the first initial positions; perform screening processing on each of the first initial index values to obtain the first optimal initial position, so as to obtain the first initial recommended goods location corresponding to the goods to be warehoused; update the first position coordinates of each of the first initial positions by using a random crossover and mutation method, and re-perform goods location screening based on the updated first position coordinates, and iterate in a loop until the number of iterations is equal to a preset threshold, and then determine the updated first initial recommended goods location as the first target goods location.

[0130] In the specific implementation process, the first screening module 2 is further configured to: when the warehouse type of the target warehouse is a stereoscopic warehouse, perform calculation processing based on the historical demand data of the goods to be warehoused within a preset time period to obtain the second demand frequency and the second demand quantity of the goods to be warehoused; perform calculation processing based on the information of the goods to be warehoused and the goods location configuration information to obtain the material quality and transfer penalty of the goods to be warehoused allocated to each goods location; perform goods location screening on the goods to be warehoused by using a preset genetic algorithm based on the second demand frequency, the second demand quantity, each of the material qualities, each of the transfer penalties, a preset third warehousing function, a preset fourth warehousing function, and a preset fifth warehousing function to obtain the first target goods location corresponding to the goods to be warehoused.

[0131] In the specific implementation process, the first screening module 2 is also used to: initialize the population based on the second demand frequency, the second demand quantity, the material quality, the transfer penalty, the preset second constraint condition and the preset optimization parameter to obtain the second initial position of each individual in the population, and the preset optimization parameter includes the number of individuals and the maximum number of iterations; based on each of the second initial positions, respectively use the third storage function, the fourth storage function and the fifth storage function to perform calculation processing to obtain the third parameter value, the fourth parameter value and the fifth parameter value corresponding to each of the second initial positions; based on the third parameter value, the fourth parameter value and the fifth parameter value corresponding to the same second initial position, perform calculation processing to obtain the second initial index value corresponding to each of the second initial positions; screen each of the second initial index values ​​to obtain the second optimal initial position, so as to obtain the second initial recommended cargo location corresponding to the goods to be stored; use the random crossover mutation method to update the second position coordinates of each of the second initial positions, and re-screen the cargo location based on the updated second position coordinates, and iterate repeatedly until the number of iterations is equal to the preset threshold, and the updated second initial recommended cargo location is determined as the first target cargo location.

[0132] In the specific implementation process, the second screening module 3 is specifically used for: when the warehouse type of the target warehouse is a flat warehouse, initializing the population based on the basic information of the materials, the information of the materials to be shipped out, the cargo location configuration information, the preset third constraint conditions and the preset optimization parameters, and obtaining the third initial position corresponding to each individual in the population; using the first outbound function and the second outbound function to calculate and process the third position coordinates of the third initial position respectively, and obtaining the first outbound index and the second outbound index; calculating and processing based on the first outbound index and the second outbound index corresponding to the same third initial position, and obtaining the third initial index value corresponding to the same third initial position; screening and processing each of the third initial index values ​​to obtain the third optimal initial position, so as to obtain the third initial recommended cargo location corresponding to the goods to be shipped out; updating the third position coordinates of each of the third initial positions by the random crossover mutation method, and re-screening the cargo location based on the updated third position coordinates, and iterating in a loop until the number of iterations is equal to the preset threshold, and the updated third initial recommended cargo location is determined as the second target cargo location.

[0133] In the specific implementation process, the second screening module 3 is also used for: when the warehouse type of the target warehouse is a stereoscopic warehouse, the population is initialized based on the basic information of the materials, the information of the materials to be shipped out, the cargo location configuration information, the preset fourth constraint condition and the preset optimization parameter to obtain the fourth initial position corresponding to each individual in the population; the third outbound function, the fourth outbound function and the fifth outbound function are respectively used for calculation and processing based on the fourth position coordinates of the fourth initial position to obtain the third outbound index, the fourth outbound index and the fifth outbound index; the third outbound index, the fourth outbound index and the fifth outbound index corresponding to the same fourth initial position are calculated and processed to obtain the fourth initial index value corresponding to the same fourth initial position; the fourth initial index values ​​are screened to obtain the fourth optimal initial position to obtain the fourth initial recommended cargo location corresponding to the goods to be shipped out; the fourth position coordinates of each fourth initial position are updated by the random crossover mutation method, and the cargo location is re-screened based on the updated fourth position coordinates, and it is iterated in a loop until the number of iterations is equal to the preset threshold, and the updated fourth initial recommended cargo location is determined as the second target cargo location.

[0134] This application obtains the basic information of materials and the cargo space configuration information of the target warehouse; when materials enter the warehouse, based on the basic information of materials, the information of materials to be entered and the cargo space configuration information, the preset entry rules corresponding to the warehouse type of the target warehouse are used to screen the cargo spaces, and the first target cargo space corresponding to the goods to be entered is obtained; when materials leave the warehouse, based on the basic information of materials, the information of materials to be left and the cargo space configuration information, the preset exit rules corresponding to the warehouse type of the target warehouse are used to screen the cargo spaces, and the second target cargo space corresponding to the goods to be left is obtained. This application automatically allocates cargo spaces through algorithms, especially the application of the close-range cargo space allocation principle and the balanced workload principle, so that the storage and retrieval of materials are more efficient, the walking distance and operation time of warehouse workers and equipment are reduced, the speed of materials entering and leaving the warehouse is increased, and congestion and waiting in the loading and unloading areas of flat warehouses and the shuttle lanes of stereoscopic warehouses are avoided, thereby significantly improving the overall efficiency of warehousing operations. It also implements the first-in-first-out principle and minimizes storage fragmentation, optimizes the selection of outbound cargo locations, and effectively solves the problems of insufficient storage utilization and stagnant inventory backlogs, so that the warehouse's storage space can be reasonably and fully utilized, maximizing storage capacity while reducing storage costs.

[0135] Another embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the following method steps are implemented:

[0136] Step 1: Obtain the basic information of materials and storage location configuration information of the target warehouse;

[0137] Step 2: When materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage, and the storage location configuration information, the preset storage rules corresponding to the warehouse type of the target warehouse are used to screen the storage locations, and the first target storage location corresponding to the materials to be put into storage is obtained;

[0138] Step 3: When materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the cargo location configuration information, the preset shipping rules corresponding to the warehouse type of the target warehouse are used to screen the cargo locations to obtain a second target cargo location corresponding to the goods to be shipped out.

[0139] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0140] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0141] The specific implementation process of the above method steps can be found in the above-mentioned embodiment of any cargo location recommendation method, and this embodiment will not be repeated here.

[0142] This application obtains the basic information of materials and the cargo space configuration information of the target warehouse; when materials enter the warehouse, based on the basic information of materials, the information of materials to be entered and the cargo space configuration information, the preset entry rules corresponding to the warehouse type of the target warehouse are used to screen the cargo spaces, and the first target cargo space corresponding to the goods to be entered is obtained; when materials leave the warehouse, based on the basic information of materials, the information of materials to be left and the cargo space configuration information, the preset exit rules corresponding to the warehouse type of the target warehouse are used to screen the cargo spaces, and the second target cargo space corresponding to the goods to be left is obtained. This application automatically allocates cargo spaces through algorithms, especially the application of the close-range cargo space allocation principle and the balanced workload principle, so that the storage and retrieval of materials are more efficient, the walking distance and operation time of warehouse workers and equipment are reduced, the speed of materials entering and leaving the warehouse is increased, and congestion and waiting in the loading and unloading areas of flat warehouses and the shuttle lanes of stereoscopic warehouses are avoided, thereby significantly improving the overall efficiency of warehousing operations. It also implements the first-in-first-out principle and minimizes storage fragmentation, optimizes the selection of outbound cargo locations, and effectively solves the problems of insufficient storage utilization and stagnant inventory backlogs, so that the warehouse's storage space can be reasonably and fully utilized, maximizing storage capacity while reducing storage costs.

[0143] Another embodiment of the present application provides an electronic device, comprising at least a memory and a processor, wherein the memory stores a computer program, and the processor implements the following method steps when executing the computer program in the memory:

[0144] Step 1: Obtain the basic information of materials and storage location configuration information of the target warehouse;

[0145] Step 2: When materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage, and the storage location configuration information, the preset storage rules corresponding to the warehouse type of the target warehouse are used to screen the storage locations, and the first target storage location corresponding to the materials to be put into storage is obtained;

[0146] Step 3: When materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the cargo location configuration information, the preset shipping rules corresponding to the warehouse type of the target warehouse are used to screen the cargo locations to obtain a second target cargo location corresponding to the goods to be shipped out.

[0147] The specific implementation process of the above method steps can be found in the above-mentioned embodiment of any cargo location recommendation method, and this embodiment will not be repeated here.

[0148] This application obtains the basic information of materials and the cargo space configuration information of the target warehouse; when materials enter the warehouse, based on the basic information of materials, the information of materials to be entered and the cargo space configuration information, the preset entry rules corresponding to the warehouse type of the target warehouse are used to screen the cargo spaces, and the first target cargo space corresponding to the goods to be entered is obtained; when materials leave the warehouse, based on the basic information of materials, the information of materials to be left and the cargo space configuration information, the preset exit rules corresponding to the warehouse type of the target warehouse are used to screen the cargo spaces, and the second target cargo space corresponding to the goods to be left is obtained. This application automatically allocates cargo spaces through algorithms, especially the application of the close-range cargo space allocation principle and the balanced workload principle, so that the storage and retrieval of materials are more efficient, the walking distance and operation time of warehouse workers and equipment are reduced, the speed of materials entering and leaving the warehouse is increased, and congestion and waiting in the loading and unloading areas of flat warehouses and the shuttle lanes of stereoscopic warehouses are avoided, thereby significantly improving the overall efficiency of warehousing operations. It also implements the first-in-first-out principle and minimizes storage fragmentation, optimizes the selection of outbound cargo locations, and effectively solves the problems of insufficient storage utilization and stagnant inventory backlogs, so that the warehouse's storage space can be reasonably and fully utilized, maximizing storage capacity while reducing storage costs.

[0149] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims

1. A flexible recommendation method for power material cargo space, characterized in that: include: Obtain basic information about materials and storage location configuration of the target warehouse; When materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage and the storage location configuration information, the preset storage rules corresponding to the warehouse type of the target warehouse are used to screen the storage locations, and the first target storage location corresponding to the materials to be put into storage is obtained; When materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the cargo location configuration information, the preset shipping rules corresponding to the warehouse type of the target warehouse are used to screen the cargo locations to obtain a second target cargo location corresponding to the goods to be shipped out.

2. The method according to claim 1, characterized in that When materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage and the storage location configuration information, the preset storage rules corresponding to the warehouse type of the target warehouse are used to screen the storage locations, and the first target storage location corresponding to the materials to be put into storage is obtained, which specifically includes: When the warehouse type of the target warehouse is a flat warehouse, a first demand frequency and a first demand quantity of the goods to be stored are obtained by performing calculations based on historical demand data of the goods to be stored in a preset period of time; Calculation and processing are performed based on the information of the materials to be stored and the cargo location configuration information to obtain first coordinate parameter information of the same type of goods corresponding to the goods to be stored and second coordinate parameter information of the different type of goods corresponding to the goods to be stored; Based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, the preset first warehousing function and the preset second warehousing function, a preset genetic algorithm is used to screen the cargo locations of the goods to be stored, so as to obtain the first target cargo location corresponding to the goods to be stored.

3. The method according to claim 2, characterized in that The method of using a preset genetic algorithm to screen the cargo locations of the goods to be stored based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, the preset first storage function, and the preset second storage function to obtain the first target storage location corresponding to the goods to be stored specifically includes: Initialize the population based on the first demand frequency, the first demand quantity, the first coordinate parameter information, the second coordinate parameter information, a preset first constraint condition, and a preset optimization parameter to obtain a first initial position of each individual in the population, wherein the preset optimization parameter includes the number of individuals and the maximum number of iterations; Based on each of the first initial positions, the first storage function and the second storage function are respectively used to perform calculation processing to obtain a first parameter value and a second parameter value corresponding to each of the first initial positions; Performing calculation processing based on the first parameter value and the second parameter value corresponding to the same first initial position to obtain a first initial index value corresponding to each first initial position; Screening the first initial index values ​​to obtain a first optimal initial position, so as to obtain a first initial recommended cargo position corresponding to the cargo to be stored; The first position coordinates of each first initial position are updated by a random crossover mutation method, and the cargo location is re-screened based on the updated first position coordinates, and the cycle is iterated until the number of iterations is equal to a preset threshold, and the updated first initial recommended cargo location is determined as the first target cargo location.

4. The method according to claim 1, characterized in that When materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage and the storage location configuration information, the preset storage rules corresponding to the warehouse type of the target warehouse are used to perform storage location screening to obtain the first target storage location corresponding to the materials to be put into storage, and further comprising: When the warehouse type of the target warehouse is a three-dimensional warehouse, a second demand frequency and a second demand quantity of the goods to be stored are obtained by performing calculation and processing based on the historical demand data of the goods to be stored in a preset period of time; Calculation is performed based on the information of the materials to be stored and the cargo location configuration information to obtain the material quality and transfer penalty of the materials to be stored allocated to each cargo location; Based on the second demand frequency, the second demand quantity, the quality of each material and the penalty for each warehouse transfer, the preset third warehousing function, the preset fourth warehousing function and the preset fifth warehousing function, a preset genetic algorithm is used to screen the storage locations of the goods to be stored, and the first target storage location corresponding to the goods to be stored is obtained.

5. The method according to claim 4, characterized in that The method of using a preset genetic algorithm to screen the cargo locations of the goods to be stored based on the second demand frequency, the second demand quantity, the quality of each material, the penalties for each warehouse transfer, the preset third storage function, the preset fourth storage function, and the preset fifth storage function to obtain the first target storage location corresponding to the goods to be stored specifically includes: Initialize the population based on the second demand frequency, the second demand quantity, the material quality, the warehouse transfer penalty, the preset second constraint condition and the preset optimization parameters to obtain the second initial position of each individual in the population, wherein the preset optimization parameters include the number of individuals and the maximum number of iterations; Based on each of the second initial positions, the third storage function, the fourth storage function and the fifth storage function are used to perform calculation processing to obtain a third parameter value, a fourth parameter value and a fifth parameter value corresponding to each of the second initial positions; Performing calculation processing based on the third parameter value, the fourth parameter value, and the fifth parameter value corresponding to the same second initial position to obtain a second initial index value corresponding to each second initial position; Screening the second initial index values ​​to obtain a second optimal initial position, so as to obtain a second initial recommended cargo position corresponding to the goods to be stored; The second position coordinates of each second initial position are updated by a random crossover mutation method, and the cargo location is re-screened based on the updated second position coordinates, and the cycle is iterated until the number of iterations is equal to a preset threshold, and the updated second initial recommended cargo location is determined as the first target cargo location.

6. The method according to claim 1, characterized in that When the materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the cargo location configuration information, a preset shipping rule corresponding to the warehouse type of the target warehouse is used to perform cargo location screening to obtain a second target cargo location corresponding to the goods to be shipped out, specifically including: When the warehouse type of the target warehouse is a flat warehouse, the population is initialized based on the basic information of the materials, the information of the materials to be shipped out, the cargo space configuration information, the preset third constraint condition and the preset optimization parameter to obtain a third initial position corresponding to each individual in the population; Based on the third position coordinates of the third initial position, the first outbound function and the second outbound function are used to perform calculation processing to obtain the first outbound index and the second outbound index; Calculate and process the first outbound index and the second outbound index corresponding to the same third initial position to obtain a third initial index value corresponding to the same third initial position; Screening the third initial index values ​​to obtain a third optimal initial position, so as to obtain a third initial recommended cargo position corresponding to the cargo to be shipped out; The third position coordinates of each of the third initial positions are updated by a random crossover mutation method, and the cargo location is re-screened based on the updated third position coordinates, and the process is iterated in a loop until the number of iterations is equal to a preset threshold, and the updated third initial recommended cargo location is determined as the second target cargo location.

7. The method according to claim 4, characterized in that When the materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the cargo location configuration information, a preset shipping rule corresponding to the warehouse type of the target warehouse is used to perform cargo location screening to obtain a second target cargo location corresponding to the goods to be shipped out, and further comprising: When the warehouse type of the target warehouse is a stereoscopic warehouse, the population is initialized based on the basic information of the materials, the information of the materials to be shipped out, the cargo space configuration information, the preset fourth constraint condition and the preset optimization parameter to obtain a fourth initial position corresponding to each individual in the population; Based on the fourth position coordinate of the fourth initial position, the third out-of-stock function, the fourth out-of-stock function and the fifth out-of-stock function are used to perform calculation processing respectively to obtain the third out-of-stock index, the fourth out-of-stock index and the fifth out-of-stock index; Calculate and process the third outbound index, the fourth outbound index, and the fifth outbound index corresponding to the same fourth initial position to obtain a fourth initial index value corresponding to the same fourth initial position; Screening the fourth initial index values ​​to obtain a fourth optimal initial position, so as to obtain a fourth initial recommended cargo position corresponding to the cargo to be shipped out; The fourth position coordinates of each of the fourth initial positions are updated by a random crossover mutation method, and the cargo location is re-screened based on the updated fourth position coordinates, and the cycle is iterated until the number of iterations is equal to a preset threshold, and the updated fourth initial recommended cargo location is determined as the second target cargo location.

8. A flexible recommendation device for power material cargo location, characterized in that: include: The acquisition module is used to obtain the basic information of materials and the storage location configuration information of the target warehouse; A first screening module is used for screening cargo locations when materials are put into storage, based on the basic information of the materials, the information of the materials to be put into storage and the cargo location configuration information, using the preset storage rules corresponding to the warehouse type of the target warehouse to obtain a first target cargo location corresponding to the goods to be put into storage; The second screening module is used to screen the cargo locations when the materials are shipped out, based on the basic information of the materials, the information of the materials to be shipped out and the cargo location configuration information, using the preset shipping rules corresponding to the warehouse type of the target warehouse to obtain the second target cargo location corresponding to the goods to be shipped out.

9. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for flexible recommendation of electric power material storage locations described in any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The method comprises at least a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method for flexible recommendation of electric power material cargo locations as described in any one of claims 1 to 7 when executing the computer program on the memory.

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