Commodity access position optimization method, system and device and storage medium

Abstract

The invention discloses a commodity access position optimization method, system and device and a storage medium. The method comprises the steps that order information is acquired, data extraction and preprocessing are performed on the order information, and the commodity demand of a store is determined; according to the commodity demanded quantity, the demanded quantity of the first type of commodities and the demanded quantity of the second type of commodities are determined through the basket fullness rate of the turnover box, and according to the demanded quantity, the first type of commodities are combined into a high-permeability commodity group, and the second type of commodities are combined into a low-permeability commodity group; determining a first area for storing a high-permeability commodity group according to a shortest moving line strategy; determining a first area and a second area for storing the low-permeability commodity group in combination with a basket fullness rate strategy of the turnover box; and according to a storage location recommendation strategy, based on the first region and the second region, determining an access storage location of each commodity in the high-permeability commodity group and the low-permeability commodity group. The embodiment of the invention is beneficial to improving the efficiency of access position planning and reducing the cost. The method can be widely applied to the technical field of path optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of path optimization, and in particular to a method, system, device and storage medium for optimizing commodity access locations. Background Art

[0002] With the rapid development of logistics and e-commerce industries, the types and quantities of goods in warehouses have increased significantly. There is a process of storage and retrieval of goods in warehouses. How to plan the storage locations of various types of goods in the storage and retrieval process to speed up the distribution process of goods and improve the efficiency of goods entering the market. In related technologies, the storage and retrieval locations of goods are usually planned based on the experience of relevant personnel, which makes the storage and retrieval process of goods more time-consuming, and it is impossible to estimate the remaining capacity of the warehouse, resulting in low utilization of the warehouse and increased circulation costs of goods. Summary of the invention

[0003] The purpose of the present invention is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0004] To this end, an object of the present invention is to provide an efficient method, system, device and storage medium for optimizing commodity access locations.

[0005] In order to achieve the above technical objectives, one aspect of an embodiment of the present invention provides a method for optimizing the storage and access locations of goods, comprising the following steps: obtaining order information, extracting and preprocessing the order information, and determining the demand for goods in the store; according to the demand for goods, determining the demand for the first category of goods and the demand for the second category of goods through the full basket rate of the turnover box, and according to the demand, merging the first category of goods into a high-penetration commodity group and merging the second category of goods into a low-penetration commodity group; the historical sales of the first category of goods are better than the historical sales of the second category of goods; according to the shortest moving line strategy, determining the first area for storing the high-penetration commodity group; combining the full basket rate strategy of the turnover box, determining the first area and the second area for storing the low-penetration commodity group; according to the storage location recommendation strategy, determining the storage and access locations of each commodity in the high-penetration commodity group and the low-penetration commodity group based on the first area and the second area. The embodiment of the present application classifies the goods according to the demand of the store, and plans the storage and access locations of the goods based on the storage location recommendation strategy, which is conducive to improving the efficiency of storage and access location planning, making full use of warehouse space, and reducing costs.

[0006] In some embodiments, the method for optimizing the storage and access positions of commodities in the embodiments of the present invention, determining the demand for the first category of commodities and the demand for the second category of commodities by the full basket rate of the turnover box according to the demand for the commodities, comprises:

[0007] According to the demand for the goods, pre-sorting the required goods based on the first category of goods and the second category of goods, and determining a first number of required turnover boxes;

[0008] Determining a full rate of the turnover box according to the commodity demand and the first quantity;

[0009] Adjusting the pre-sorting process to obtain a number of full basket rates;

[0010] An optimal full basket rate among the plurality of full basket rates is determined, and based on a pre-sorting method corresponding to the optimal full basket rate, a demand for the first category of goods and a demand for the second category of goods are determined.

[0011] In some embodiments, in an embodiment of the present invention, the method of pre-sorting the required commodities based on the first category of commodities and the second category of commodities according to the commodity demand, and determining the first number of required turnover boxes includes:

[0012] If the pre-sorted turnover box matches the maximum loading percentage set for the turnover box, determine that the quantity of goods sorted to each of the turnover boxes is less than or equal to the loading quantity corresponding to the maximum loading percentage;

[0013] Alternatively, if the pre-sorted turnover boxes do not match the maximum loading percentage set for the turnover boxes, it is determined that the quantity of goods sorted to each of the turnover boxes is less than or equal to the basic loading capacity of the turnover box.

[0014] In some embodiments, in an embodiment of the present invention, the determining of the first area and the second area for storing the low-permeability commodity group in combination with the full basket rate strategy of the turnover box includes:

[0015] If there are turnover boxes in the first area whose full basket rate is less than or equal to the preset full basket rate, some of the goods in the low-permeability goods group are placed in the first area;

[0016] Alternatively, if the full basket rates of the turnover boxes in the first area are all greater than a preset full basket rate, the unsorted goods in the low-permeability commodity group are placed in the second area.

[0017] In some embodiments, in an embodiment of the present invention, determining the storage and access storage location of each commodity in the high-penetration commodity group and the low-penetration commodity group based on the first area and the second area according to the storage location recommendation strategy includes:

[0018] If the current commodity exists in a stock location in the first area or the second area and the stock location meets the storage capacity, place the current commodity in the stock location;

[0019] If there is an adjacent storage location to the in-stock storage location, the adjacent storage location meets the storage capacity, and there are no similar products in the surrounding storage locations of the adjacent storage location, the current product is placed in the adjacent storage location; or, if there is an adjacent storage location to the in-stock storage location, the adjacent storage location meets the storage capacity, and there are similar products in the surrounding storage locations of the adjacent storage location, the current product is placed in the first storage location that is separated from the similar product by a preset storage location distance;

[0020] The storage and access location is determined according to the attributes of the current commodity.

[0021] In some embodiments, in an embodiment of the present invention, determining the storage and access location according to the attributes of the current commodity includes:

[0022] If the current product is a hot item and there is a first historical empty storage location, the storage and access storage location is determined based on whether there are similar products in the surrounding storage locations of the first historical empty storage location; or, if the current product is a hot item and there is no first historical empty storage location, the storage and access storage location is determined based on a constraint condition; the constraint condition is to limit the storage and access storage location of the product based on the attributes of the product;

[0023] If the current commodity is a large item and there is a second historical empty storage location, the access storage location is determined based on whether there are similar commodities in the surrounding storage locations of the second historical empty storage location; or, if the current commodity is a large item and there is no second historical empty storage location, the access storage location is determined based on the constraint condition;

[0024] If the current commodity is a heavy object and there is a third historical empty storage location, the access storage location is determined based on whether there are similar commodities in the surrounding storage locations of the third historical empty storage location; or, if the current commodity is a heavy object and there is no third historical empty storage location, the access storage location is determined based on the constraint condition;

[0025] The storage and access locations are determined according to the categories of the commodities.

[0026] In some embodiments, in one embodiment of the present invention, the method further comprises:

[0027] If the current product is a new product in the warehouse, the process returns to the step of determining the access location based on whether there are similar products in the surrounding locations of the second historical empty location if the current product is a large item and there is a second historical empty location.

[0028] On the other hand, an embodiment of the present invention provides a commodity storage and access location optimization system, including:

[0029] The first module is used to obtain order information, perform data extraction and preprocessing on the order information, and determine the demand for goods in the store;

[0030] The second module is used to determine the demand for the first category of goods and the demand for the second category of goods according to the full basket rate of the turnover box according to the demand for the goods, and merge the first category of goods into a high-penetration goods group and merge the second category of goods into a low-penetration goods group according to the demand; the historical sales volume of the first category of goods is better than the historical sales volume of the second category of goods;

[0031] The third module is used to determine the first area for storing the high-permeability commodity group according to the shortest moving line strategy; and determine the first area and the second area for storing the low-permeability commodity group in combination with the turnover box full basket rate strategy;

[0032] The fourth module is used to determine the storage location of each commodity in the high-penetration commodity group and the low-penetration commodity group based on the first area and the second area according to the storage location recommendation strategy.

[0033] On the other hand, an embodiment of the present invention provides a device for optimizing a commodity storage and access location, comprising:

[0034] at least one processor;

[0035] at least one memory for storing at least one program;

[0036] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned commodity access location optimization method.

[0037] On the other hand, an embodiment of the present invention provides a storage medium storing a program executable by a processor, wherein the program executable by the processor is used to implement the above-mentioned commodity access location optimization method when executed by the processor.

[0038] The embodiments of the present application include at least the following beneficial effects: The method provided by the embodiments of the present invention includes: obtaining order information, extracting and preprocessing the order information, and determining the demand for goods in the store; according to the demand for goods, determining the demand for the first category of goods and the demand for the second category of goods through the full basket rate of the turnover box, and according to the demand, merging the first category of goods into a high-penetration commodity group and merging the second category of goods into a low-penetration commodity group; the historical sales volume of the first category of goods is better than the historical sales volume of the second category of goods; according to the shortest moving line strategy, determining the first area for storing the high-penetration commodity group; combining the full basket rate strategy of the turnover box, determining the first area and the second area for storing the low-penetration commodity group; according to the storage location recommendation strategy, based on the first area and the second area, determining the storage and access locations of each commodity in the high-penetration commodity group and the low-penetration commodity group. The embodiments of the present application classify the goods according to the demand of the store, and plan the storage and access locations of the goods based on the storage location recommendation strategy, which is conducive to improving the efficiency of storage and access location planning, making full use of warehouse space, and reducing costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the embodiments of the present invention or the drawings of related technical solutions in the prior art are introduced below. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for optimizing commodity storage and access locations provided by the present invention;

[0041] Figure 2 A schematic diagram of a flow chart of an embodiment of a commodity grading process provided by the present invention;

[0042] Figure 3 A schematic diagram of a flow chart of another embodiment of a method for optimizing commodity access locations provided by the present invention;

[0043] Figure 4 A schematic diagram of a flow chart of an embodiment of a commodity attribute classification process provided by the present invention;

[0044] Figure 5 A schematic diagram of the structure of an embodiment of the commodity storage and access location optimization system provided by the present invention;

[0045] Figure 6 A schematic structural diagram of an embodiment of a device for optimizing commodity access locations provided by the present invention. DETAILED DESCRIPTION

[0046] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limitations of the present invention. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0047] The warehouse access in the related technology relies on the experience of relevant personnel, which is slow: data clerks manually arrange the access to the warehouse, which takes nearly 2 hours per time, highly dependent on personal experience, and the operation speed is slow. High cost: It is impossible to accurately calculate the remaining capacity of the warehouse, and the utilization rate of the warehouse space is low, resulting in increased warehouse use costs. Low efficiency: The storage locations of goods lack scientific management, resulting in repeated access paths and long movement lines for goods, and low operation efficiency.

[0048] Specifically, from the perspective of system design, the basic information of goods and storage locations will affect the actual recommendation results. If the basic attributes of goods or storage locations are wrong or missing, the recommendation results will be inaccurate. If there are differences in the layout, storage location arrangement, and storage location generation rules of each warehouse, it will also affect the actual recommendation results of the recommended storage locations.

[0049] In short, with the rapid development of logistics and e-commerce industries, the types and quantities of goods in warehouses have increased significantly. The existing scheduling methods have made the storage and retrieval process of goods more complicated. The intelligent storage and retrieval scheduling problem of inventory goods belongs to the path optimization problem of goods storage and sorting out of the warehouse.

[0050] Specifically, from the algorithm level: the first adaptation algorithm is used to solve the problems of mixed and random storage of goods, as well as the optimization of the path of goods sorting out of the warehouse. System level: there is currently no available system support, and at this stage, it actually relies on the warehouse staff's familiarity with the storage location and goods for pre-arrangement.

[0051] Based on this, this application recommends storage location solutions through the system to solve the problems of time-consuming manual scheduling, reducing strong dependence on manual experience, and low storage utilization, optimize the storage and access paths of goods, reduce the repeated routes of operators, shorten the operation paths, and improve overall operation efficiency. Optimize the pickup path, shorten the operation path and movement line. By dynamically calculating the allocation rules of high-penetration and low-penetration products, the full frame rate of turnover boxes can be increased and transportation costs can be reduced.

[0052] The following describes in detail a method and system for optimizing a commodity access position according to an embodiment of the present invention with reference to the accompanying drawings. First, a method for optimizing a commodity access position according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0053] Reference Figure 1 In an embodiment of the present invention, a method for optimizing the access location of goods is provided. The method for optimizing the access location of goods in the embodiment of the present invention can be applied to a terminal, or to a server, or can be software running in a terminal or a server, etc. The terminal can be a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The server can be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, as well as big data and artificial intelligence platforms. The method for optimizing the access location of goods in the embodiment of the present invention mainly includes the following steps:

[0054] S100: Obtain order information, extract and pre-process the order information, and determine the demand for goods in the store;

[0055] S200: According to the demand for the goods, the demand for the first category of goods and the demand for the second category of goods are determined by the full basket rate of the turnover box, and according to the demand, the first category of goods are merged into a high-penetration product group, and the second category of goods are merged into a low-penetration product group; the historical sales volume of the first category of goods is better than the historical sales volume of the second category of goods;

[0056] S300: Determine the first area for storing the high-permeability commodity group according to the shortest moving line strategy; determine the first area and the second area for storing the low-permeability commodity group in combination with the turnover box full basket rate strategy;

[0057] S400: Determine the storage location of each commodity in the high-penetration commodity group and the low-penetration commodity group based on the first area and the second area according to the storage location recommendation strategy.

[0058] In some possible implementations, the first category of goods and the second category of goods are divided according to the historical sales volume of the goods. Of course, the first category of goods and the second category of goods can also be divided according to consumer acceptance, or according to historical reservations, or according to revenue. This application does not limit the specific way of classifying goods. It should be noted that, with reference to Figure 2 As shown, the first category of goods in the embodiment of the present application can be Figure 2 The second category of goods is Figure 2 Class C in. Figure 2It is an illustrative example and is not intended to limit the classification of commodities. It is understandable that the first category of commodities in the embodiment of the present application may represent two categories of commodities, three categories of commodities, or multiple categories of commodities. Similarly, the second category of commodities does not limit the number of commodity categories.

[0059] In some embodiments, the shortest route strategy in the present application is related to the warehouse layout. The storage location recommendation strategy is related to the attributes of the goods. The first area and the second area both include a number of storage locations.

[0060] Optionally, in one embodiment of the present invention, according to the demand for commodities, the demand for the first category of commodities and the demand for the second category of commodities are determined by the full rate of the turnover box, including:

[0061] According to the demand for goods, pre-sort the required goods based on the first category of goods and the second category of goods, and determine the first quantity of required turnover boxes;

[0062] Determine the full rate of the turnover box based on the demand for goods and the first quantity;

[0063] Adjust the pre-sorting process to obtain a certain basket full rate;

[0064] An optimal full basket rate among several full basket rates is determined, and based on a pre-sorting method corresponding to the optimal full basket rate, a demand for the first category of goods and a demand for the second category of goods are determined.

[0065] Optionally, in one embodiment of the present invention, according to the demand for commodities, the required commodities are pre-sorted based on the first category commodities and the second category commodities, and the first quantity of required turnover boxes is determined, including:

[0066] If the pre-sorted turnover box matches the maximum loading percentage set for the turnover box, determine that the quantity of goods sorted to each turnover box is less than or equal to the loading quantity corresponding to the maximum loading percentage;

[0067] Alternatively, if the pre-sorted totes do not match the maximum loading percentage set for the totes, it is determined that the quantity of merchandise sorted to each tote is less than or equal to the basic loading capacity of the tote.

[0068] In some possible implementations, the maximum loading percentage of the turnover box is a parameter of the turnover box, and there is no fixed standard value. It depends on the type of turnover box (such as plastic turnover box, paper turnover box, etc.), size, shape, design purpose and characteristics of the items contained (shape, weight, whether it is fragile, etc.). For example, for products with regular shape and hard texture, it may be possible to fill up to about 90%-95% of the space utilization rate; but if it is some irregular and fragile items, in order to prevent damage, the maximum loading capacity may only be about 70%-80%. The basic loading capacity of the turnover box varies depending on factors such as the size, shape and purpose of the turnover box. In terms of shape, square turnover boxes are relatively regular and the calculation of capacity is relatively simple, while some special-shaped turnover boxes (such as those with special curvatures or irregular corners) will determine the capacity based on their actual internal space. In addition, if the turnover box is used to load liquids, the calculation method of the effective capacity is also different from that of loading solid goods. When loading liquids, the internal volume of the turnover box is mainly considered, and when loading solids, the stacking method of the solids also needs to be considered.

[0069] Optionally, in one embodiment of the present invention, in combination with the full basket rate strategy of the turnover box, determining the first area and the second area for storing the low-permeability commodity group includes:

[0070] If there are turnover boxes in the first area whose full basket rate is less than or equal to the preset full basket rate, some of the products in the low-permeability product group are placed in the first area;

[0071] Alternatively, if the full basket rates of the turnover boxes in the first area are all greater than the preset full basket rate, the unsorted goods in the low-penetration product group are placed in the second area.

[0072] In some possible implementations, low-permeability group commodities are preferentially used to fill turnover boxes with insufficient full basket rate in the first area, and then placed in the second area set up for low-permeability commodities.

[0073] Optionally, in one embodiment of the present invention, according to the storage location recommendation strategy, based on the first area and the second area, determining the storage and access location of each commodity in the high-penetration commodity group and the low-penetration commodity group includes:

[0074] If the current product exists in the first area or the second area and the storage location meets the storage capacity, the current product is placed in the storage location;

[0075] If there is an adjacent storage location in the warehouse, the adjacent storage location meets the storage capacity, and there are no similar products in the surrounding storage locations of the adjacent storage location, the current product is placed in the adjacent storage location; or, if there is an adjacent storage location in the warehouse, the adjacent storage location meets the storage capacity, and there are similar products in the surrounding storage locations of the adjacent storage location, the current product is placed in the first storage location that is separated from the similar product by a preset storage location distance;

[0076] Determine the storage and access location based on the attributes of the current product.

[0077] In some possible implementations, the current product has been placed in the first area or the second area of ​​the warehouse, and the warehouse location of the current product has been placed; the preset warehouse location distance is the distance measured in warehouse locations, such as the first warehouse location that is one warehouse location away from similar products, and the first warehouse location that is two warehouse locations away from similar products. Figure 3 The flowchart shown in the figure prioritizes the existence of in-stock storage locations and adjacent storage locations, and then places the products in the order of popular items, large items, and heavy items in the attributes.

[0078] Optionally, in one embodiment of the present invention, determining the storage and access location according to the attributes of the current commodity includes:

[0079] If the current product is a hot item and there is a first historical empty storage location, the storage and access storage location is determined based on whether there are similar products in the surrounding storage locations of the first historical empty storage location; or, if the current product is a hot item and there is no first historical empty storage location, the storage and access storage location is determined based on the constraint conditions; the constraint conditions are to limit the storage and access storage locations of the product based on the attributes of the product;

[0080] If the current product is a large item and there is a second historical empty storage location, the storage and access location is determined based on whether there are similar products in the surrounding storage locations of the second historical empty storage location; or, if the current product is a large item and there is no second historical empty storage location, the storage and access location is determined based on the constraint conditions;

[0081] If the current commodity is a heavy item and there is a third historical empty storage location, the storage and access location is determined based on whether there are similar commodities in the surrounding storage locations of the third historical empty storage location; or, if the current commodity is a heavy item and there is no third historical empty storage location, the storage and access location is determined based on the constraint conditions;

[0082] Determine the storage and access locations based on the category of the merchandise.

[0083] In some possible implementations, the first historical empty storage location is a storage location that has stored popular products, or a storage location that has stored the current product.

[0084] Optionally, in one embodiment of the present invention, the method further comprises:

[0085] If the current product is a new product, return to the step of determining the storage and access location based on whether there are similar products in the surrounding locations of the second historical empty location if the current product is a large item and there is a second historical empty location.

[0086] In some possible implementations, the newly-stocked goods may be goods of a new type, which have not been purchased before.

[0087] The optimization method provided by the present application is described in detail below with a specific embodiment, specifically:

[0088] Description of the recommended storage and access location solution. This application also provides information and configuration, including the following aspects:

[0089] Basic information includes but is not limited to:

[0090] (1) Product data maintenance: When the upstream SAP pushes product files, it is necessary to maintain the volume and weight of individual products and the entire unit in the product files to provide calculation support for the full box rate of the turnover box.

[0091] (2) Storage location data maintenance: Each warehouse independently maintains warehouse data, storage location attributes, storage location capacity, etc. based on the actual warehouse layout.

[0092] (3) Maintenance of turnover box data: According to the turnover box standards used in actual business, the basic loading capacity of the turnover box is regularly maintained to provide a basis for calculating the full frame rate of the turnover box.

[0093] (4) Maintain picking path data: maintain the order and priority of product access paths based on the actual shelf layout of each warehouse.

[0094] (5) Upstream order data maintenance: record the order data pushed by the upstream, regularly analyze and label the sales data according to the algorithm, and provide a basis for storage location recommendations.

[0095] Personalized configuration includes but is not limited to:

[0096] (1) Based on the basic attributes of the products, the standards and thresholds for large items, heavy items, and popular products can be flexibly set.

[0097] (2) You can set product A, B, and C grade standards and thresholds, and dynamically calculate based on product sales and turnover rates.

[0098] (3) You can set up files for similar items and manage them by product category, shelf number, or manual configuration.

[0099] (4) The maximum loading percentage of the turnover box can be set to control the amount of goods allocated when calculating the full frame rate of the turnover box. Among them, the allocatable capacity of the turnover box = maximum loading percentage * basic loading capacity.

[0100] The data preprocessing provided in the embodiment of the present application includes the following aspects:

[0101] Product attribute label: According to the product files pushed by the upstream, obtain the basic attributes of the product, match the attribute standards and thresholds of the personalized configuration, and label the product. Figure 4 As shown, an embodiment of commodity attribute classification.

[0102] Product grade label: Dynamically obtain the sales data of the product in the past 7 days, match the personalized grade standards and thresholds, and label the products.

[0103] The implementation steps of this application optimization plan include:

[0104] First, the priority strategies include:

[0105] (1) Priority is given to historically available storage locations:

[0106] When executing the first adaptation algorithm, if the current conditions are matched, the constraints are checked among the storage locations that meet the current conditions, and historical storage locations are preferentially searched for for recommendation.

[0107] (2) Priority is given to adjacent shared storage locations:

[0108] If the storage capacity of the recommended storage location is insufficient and it matches the conditions of the current step, the constraints are checked among the storage locations that meet the corresponding conditions, and adjacent shared storage locations are prioritized for recommendation.

[0109] Second, the constraints include:

[0110] (1) Match the attributes of the product configuration. If the product label is heavy, large, or popular, it can only be placed on the first floor of the shelf or promoted on the ground;

[0111] (2) Match the level of product configuration. If the product level is A or B and it is not a large, heavy, or popular product, it can only be placed on the 2nd or 3rd floor of the shelf for quick picking.

[0112] (3) Match the level of product configuration. If the product level is C and it is not a large, heavy, or popular product, it can only be placed on the 4th floor of the shelf.

[0113] (4) Match the product attributes of the category, product number, and manually maintained similar product files. If the products stored in adjacent storage locations are similar products, recommendations need to be made with an interval of 2 storage locations.

[0114] (5) Match the maximum loading percentage set for the turnover box. When calculating the weekly box full frame rate, limit the amount of goods allocated to each turnover box to not exceed the maximum loading percentage.

[0115] (6) If the maximum loading percentage set for the turnover box cannot be matched, when calculating the full frame rate of the turnover box, the amount of goods allocated to each turnover box is limited to not exceeding the basic loading capacity of the turnover box.

[0116] (7) Match the level of product configuration. Products with a product level of C are used as dynamic allocation products and dynamically allocated to product groups with insufficient full frame rates.

[0117] Reference Figure 3 As shown, the specific implementation steps are:

[0118] Step 1: Order information is pushed upstream, and the system automatically processes order data, obtains product data after data cleaning, calculates the demand for order products and stores, and passes the product code to the system to execute the storage location recommendation process.

[0119] Step 2: The system reads the product information and analyzes the product's periodic historical sales data, and classifies and labels the products according to the preset product attributes and product level configurations.

[0120] Step 3: The system processes the store demand data, calculates the store's commodity demand, calculates the demand for Class A and B commodities through the full-box rate of the turnover box, merges them into a high-penetration commodity group, calculates the demand for Class C commodities, merges them into a low-penetration commodity group, and sets them as a dynamic allocation group. Among them, the turnover basket full-box rate: refers to the sum of the volumes of all commodities ordered by the store and the comparison value of the total volume of the sorting and storage boxes. When the full-box rate is high, it means that the number of boxes needed by the store is lower, and the fewer boxes (the higher the full-box rate), the better, and the lower the cost. Use the store order quantity to calculate the optimal value of the box full-box rate after sorting (the minimum amount of boxes used) to dynamically combine the commodities and divide the areas.

[0121] Step 4: Calculate the store demand for order information, uniformly allocate store demand to the storage and access areas of the warehouse, use the shortest route algorithm to specify storage locations in the storage and access areas for high-penetration product groups, and dynamically execute the weekly packing full basket rate algorithm to allocate low-penetration product groups to storage locations in the designated storage and access areas.

[0122] It should be noted that the warehouse area will be divided into two areas according to the principle of the highest full-frame rate and the highest penetration rate of the ordered goods. One is the high-penetration goods area, and the other is the low-penetration goods area. When sorting, the high-penetration area will be prioritized, but the goods in the high-penetration area may not fill all the boxes, so additional low-penetration goods will be added to the box to make the box hold more things. That is, for goods in the low-penetration area, they will be preferentially allocated to the storage locations with insufficient full-frame rates in the first area.

[0123] Step 5: Enter a single product code in the product group to execute the algorithm. In the storage location of the specified access area, determine whether the product is a newly added product. If it is a newly added product, jump directly to step 8 for execution.

[0124] Step 6: Based on the rule-based heuristic algorithm, check whether there is an inventory location for the product in the warehouse at the designated storage and access area, and give priority to recommending the existing inventory locations for the product.

[0125] Step 7: If step 6 is not satisfied, match the product attribute tags to determine whether the product meets the attributes of a hot-selling item. If so, and if the constraints are met, recommend a hot-selling item storage location. Specifically, conditional judgment can be performed according to the order of the constraints.

[0126] Step 8: If step 7 is not met, match the product attributes to determine whether the product meets the large or heavy attributes. If so, and if the constraints are met, recommend the floor storage or shelf 1 floor storage location.

[0127] Step 9: If step 8 is not satisfied, match the product level. If it is a product of category A or B and meets the constraints, recommend the storage location on shelf 2 or 3. If it is a product of category C and meets the constraints, recommend the storage location on shelf 4.

[0128] Step 10: Determine whether the current product has completed the storage location recommendation. If it has, pass in the next product code for execution. If it has not, check the constraints and recommend an empty storage location for recommendation. If all products have been executed, stop executing the recommendation algorithm.

[0129] It should be noted that when putting goods on the shelves, it is not mandatory for the staff to put the goods on the shelves in the recommended designated storage location. They can be put on the shelves in other available storage locations according to the actual needs of the warehouse and updated in the WMS system. The manually selected storage location will also be used as the basis for the system to recommend the next storage location for this product.

[0130] After specifying the access area, the location recommendation process is performed within the assigned access area.

[0131] The first adaptation algorithm is applied in this application: using the first adaptation algorithm, combined with the attributes of goods and storage locations, dynamically calculate the optimal solution for the storage and access path of goods, significantly improving picking efficiency and warehouse operation flexibility. Dynamic calculation of product sales: by dynamically calculating product sales in real time, matching the grade attributes of goods with the storage location floors, accurately recommending the best floor for shelving and storage of goods, thereby optimizing space utilization and storage efficiency. Intelligent sorting recommendation strategy: introducing intelligent sorting recommendation strategy, automatically adjusting the sorting strategy according to order characteristics and product characteristics, reducing manual intervention, and improving order processing speed and accuracy. Historical data-driven decision-making: based on historical data and real-time information, building a data-driven decision support system to realize intelligent inventory management and adjustment, reduce inventory costs, and improve capital turnover. Multi-dimensional commodity clustering algorithm: applying a multi-dimensional clustering algorithm, similar goods are clustered and stored, reducing the moving distance during picking, improving picking efficiency, and reducing human resource consumption. Pick-up full-frame rate algorithm: By dynamically calculating the allocation rules of high-penetration and low-penetration products, the full-frame rate during pickup is optimized, the space utilization rate during each picking is maximized, the number of pickups is reduced, and operational efficiency is improved.

[0132] In terms of labor efficiency, the embodiments of the present application can directly replace the work of data clerks in warehouse location scheduling, saving 2 hours of warehouse location scheduling workload every day; the high-penetration commodity aggregation strategy improves the efficiency of storage and access operations. In terms of paths, the commodity turnover rate, sorting full frame rate and warehouse location attributes are combined to optimize the storage and access paths of commodities, and solve the problems of repeated paths and long moving lines in the operation process. In terms of accuracy, automated warehouse location management reduces human intervention, improves operational efficiency, reduces error rates, and improves the accuracy of warehouse operations. In terms of systems, by intelligently recommending the storage and access locations of commodities, the path optimization problem of commodity shelving and storage and sorting out of the warehouse is solved, avoiding the problem that manual experience cannot calculate the capacity of the warehouse location, and the quantity and classification of commodities change at any time. At the same time, by optimizing the access paths and improving the utilization rate of warehouse space, the operating efficiency is maximized and the cost of warehouse use is reduced.

[0133] In summary, the method provided by the embodiment of the present application includes: obtaining order information, extracting and preprocessing the order information, and determining the demand for goods in the store; according to the demand for goods, determining the demand for the first category of goods and the demand for the second category of goods through the full basket rate of the turnover box, and according to the demand, merging the first category of goods into a high-penetration commodity group and merging the second category of goods into a low-penetration commodity group; the historical sales volume of the first category of goods is better than the historical sales volume of the second category of goods; according to the shortest movement line strategy, determining the first area for storing the high-penetration commodity group; combining the full basket rate strategy of the turnover box, determining the first area and the second area for storing the low-penetration commodity group; according to the storage location recommendation strategy, based on the first area and the second area, determining the storage and access locations of each commodity in the high-penetration commodity group and the low-penetration commodity group. The embodiment of the present application classifies the goods according to the demand of the store, and plans the storage and access locations of the goods based on the storage location recommendation strategy, which is conducive to improving the efficiency of storage and access location planning, making full use of warehouse space, and reducing costs.

[0134] Secondly, refer to the attached Figure 5 A commodity storage and access location optimization system proposed according to an embodiment of the present invention is described.

[0135] Figure 5 1 is a schematic diagram of the structure of a commodity storage and access location optimization system according to an embodiment of the present invention. The system specifically includes:

[0136] The first module 510 is used to obtain order information, perform data extraction and preprocessing on the order information, and determine the demand for goods in the store;

[0137] The second module 520 is used to determine the demand for the first category of goods and the demand for the second category of goods according to the full basket rate of the turnover box according to the demand for the goods, and merge the first category of goods into a high-penetration goods group and merge the second category of goods into a low-penetration goods group according to the demand; the historical sales volume of the first category of goods is better than the historical sales volume of the second category of goods;

[0138] The third module 530 is used to determine the first area for storing the high-permeability commodity group according to the shortest moving line strategy; and determine the first area and the second area for storing the low-permeability commodity group in combination with the turnover box full basket rate strategy;

[0139] The fourth module 540 is used to determine the storage location of each commodity in the high-penetration commodity group and the low-penetration commodity group based on the first area and the second area according to the storage location recommendation strategy.

[0140] It can be seen that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0141] Reference Figure 6 The embodiment of the present invention provides a device for optimizing commodity storage and access positions, comprising:

[0142] at least one processor 410;

[0143] At least one memory 420, used to store at least one program;

[0144] When the at least one program is executed by the at least one processor 410, the at least one processor 410 implements the commodity access location optimization method.

[0145] Similarly, the contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0146] An embodiment of the present invention further provides a computer-readable storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to execute the above-mentioned commodity access location optimization method.

[0147] Similarly, the contents of the above method embodiments are all applicable to the present storage medium embodiments. The functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0148] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part for which is described as a larger operation is performed independently.

[0149] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0150] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several programs to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0151] The logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable programs for implementing the logical functions, and may be embodied in any computer-readable medium for use by a program execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch and execute a program from a program execution system, device or apparatus), or in conjunction with such program execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by a program execution system, device or apparatus, or in conjunction with such program execution systems, devices or apparatuses.

[0152] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0153] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable program execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0154] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0155] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0156] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A method for optimizing commodity storage and access locations, characterized in that: The following steps are involved: Obtain order information, perform data extraction and preprocessing on the order information, and determine the demand for goods in the store; According to the demand for the goods, the demand for the first category of goods and the demand for the second category of goods are determined by the full basket rate of the turnover box, and according to the demand, the first category of goods are merged into a high-penetration goods group, and the second category of goods are merged into a low-penetration goods group; the historical sales volume of the first category of goods is better than the historical sales volume of the second category of goods; According to the shortest moving line strategy, determine the first area for storing the high-permeability commodity group; combined with the turnover box full basket rate strategy, determine the first area and the second area for storing the low-permeability commodity group; According to the storage location recommendation strategy, based on the first area and the second area, the storage and access location of each commodity in the high-penetration commodity group and the low-penetration commodity group is determined.

2. The method for optimizing the storage and access location of goods according to claim 1, characterized in that: The method of determining the demand for the first category of goods and the demand for the second category of goods by the full basket rate of the turnover box according to the demand for the goods includes: According to the demand for the goods, pre-sorting the required goods based on the first category of goods and the second category of goods, and determining a first number of required turnover boxes; Determining a full rate of the turnover box according to the commodity demand and the first quantity; Adjust the pre-sorting process to obtain a certain basket full rate; An optimal full basket rate among the plurality of full basket rates is determined, and based on a pre-sorting method corresponding to the optimal full basket rate, a demand for the first category of goods and a demand for the second category of goods are determined.

3. The method for optimizing the storage and access location of goods according to claim 2, characterized in that: The step of pre-sorting the required commodities based on the first category of commodities and the second category of commodities according to the commodity demand, and determining a first quantity of required turnover boxes includes: If the pre-sorted turnover box matches the maximum loading percentage set for the turnover box, determine that the quantity of goods sorted to each of the turnover boxes is less than or equal to the loading quantity corresponding to the maximum loading percentage; Alternatively, if the pre-sorted turnover boxes do not match the maximum loading percentage set for the turnover boxes, it is determined that the quantity of goods sorted to each of the turnover boxes is less than or equal to the basic loading capacity of the turnover box.

4. The method for optimizing the storage and access location of goods according to claim 1, characterized in that: The method of determining the first area and the second area for storing the low-permeability commodity group in combination with the full basket rate strategy of the turnover box includes: If there are turnover boxes in the first area whose full basket rate is less than or equal to the preset full basket rate, some of the goods in the low-permeability goods group are placed in the first area; Alternatively, if the full basket rates of the turnover boxes in the first area are all greater than a preset full basket rate, the unsorted goods in the low-permeability commodity group are placed in the second area.

5. The method for optimizing the storage and access location of goods according to claim 1, characterized in that: The step of determining the storage and access storage location of each commodity in the high-penetration commodity group and the low-penetration commodity group based on the first area and the second area according to the storage location recommendation strategy includes: If the current commodity exists in a stock location in the first area or the second area and the stock location meets the storage capacity, place the current commodity in the stock location; If there is an adjacent storage location to the in-stock storage location, the adjacent storage location meets the storage capacity, and there are no similar products in the surrounding storage locations of the adjacent storage location, the current product is placed in the adjacent storage location; or, if there is an adjacent storage location to the in-stock storage location, the adjacent storage location meets the storage capacity, and there are similar products in the surrounding storage locations of the adjacent storage location, the current product is placed in the first storage location that is separated from the similar product by a preset storage location distance; The storage and access location is determined according to the attributes of the current commodity.

6. The method for optimizing the storage and access location of goods according to claim 5, characterized in that: Determining the storage and access location according to the attributes of the current commodity includes: If the current product is a hot item and there is a first historical empty storage location, the storage and access storage location is determined based on whether there are similar products in the surrounding storage locations of the first historical empty storage location; or, if the current product is a hot item and there is no first historical empty storage location, the storage and access storage location is determined based on a constraint condition; the constraint condition is to limit the storage and access storage location of the product based on the attributes of the product; If the current commodity is a large item and there is a second historical empty storage location, the access storage location is determined based on whether there are similar commodities in the surrounding storage locations of the second historical empty storage location; or, if the current commodity is a large item and there is no second historical empty storage location, the access storage location is determined based on the constraint condition; If the current commodity is a heavy object and there is a third historical empty storage location, the access storage location is determined based on whether there are similar commodities in the surrounding storage locations of the third historical empty storage location; or, if the current commodity is a heavy object and there is no third historical empty storage location, the access storage location is determined based on the constraint condition; The storage and access locations are determined according to the categories of the commodities.

7. The method for optimizing the storage and access location of goods according to claim 6, characterized in that: The method further comprises: If the current product is a new product in the warehouse, the process returns to the step of determining the access location based on whether there are similar products in the surrounding locations of the second historical empty location if the current product is a large item and there is a second historical empty location.

8. A commodity storage and access location optimization system, characterized in that: include: The first module is used to obtain order information, perform data extraction and preprocessing on the order information, and determine the demand for goods in the store; The second module is used to determine the demand for the first category of goods and the demand for the second category of goods according to the full basket rate of the turnover box according to the demand for the goods, and merge the first category of goods into a high-penetration goods group and merge the second category of goods into a low-penetration goods group according to the demand; the historical sales volume of the first category of goods is better than the historical sales volume of the second category of goods; The third module is used to determine the first area for storing the high-penetration commodity group according to the shortest movement route strategy; In combination with the full basket rate strategy of the turnover box, determine the first area and the second area for storing the low-permeability commodity group; The fourth module is used to determine the storage location of each commodity in the high-penetration commodity group and the low-penetration commodity group based on the first area and the second area according to the storage location recommendation strategy.

9. A device for optimizing the storage and access position of goods, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the commodity access location optimization method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the commodity access location optimization method according to any one of claims 1 to 7 when executed by the processor.

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