A traditional Chinese medicine decoction piece warehouse-out optimization method, device, equipment and medium

Abstract

The application discloses a traditional Chinese medicine decoction piece warehouse-out optimization method, device, equipment and medium, and comprises the following steps: obtaining the cargo quantity information in a user order of traditional Chinese medicine decoction pieces, distributing the user order to a corresponding warehouse area for picking according to the cargo quantity information; respectively calculating the distance between each element in the whole piece area and the scattered piece area; according to the distance between each element, taking the path constraint and the cargo grid constraint as constraint conditions, taking the minimum distance of the picking order completion picking as a target function, respectively establishing a picking shortest path model of the whole piece area and the scattered piece area, and solving the picking shortest path by using a genetic algorithm. The application accelerates the warehouse-out process by picking in a small area, and the order with a large purchase quantity is picked out by whole pieces, which can adapt to the particularity of the traditional Chinese medicine decoction piece order, reduce the labor cost, increase the warehouse-out efficiency, and provide the warehouse-out time efficiency guarantee for the medicine supply chain of customers.

Description

A method, apparatus, equipment, and medium for optimizing the outbound processing of traditional Chinese medicine decoction pieces. Technical Field

[0001] This invention belongs to the field of outbound management technology, specifically relating to an optimized method, device, equipment, and medium for outbound processing of traditional Chinese medicine decoction pieces. Background Technology

[0002] With the booming development of e-commerce, online shopping orders have become the mainstream business model across various industries. For example, in the field of traditional Chinese medicine (TCM) decoction pieces, warehouses, as crucial transit points for these products, handle a series of operations including receiving, storing, managing, picking, and dispatching goods. Therefore, optimizing warehouse operations is of great significance for improving warehouse efficiency.

[0003] Currently, the warehousing model of conventional Chinese medicine e-commerce companies is basically the same as that of Western medicine. The outbound process still follows the conventional e-commerce warehousing and delivery model. The delivery process is generally as follows: accept customer orders---the warehouse issues picking list---picking---verification---packing. Among them, unless it is a large hospital or pharmaceutical company purchasing in bulk, most customers purchase small quantities of Chinese medicine, but there are many different types. At present, it is not possible to effectively optimize the picking path for warehouses with multiple verification stations, resulting in excessive picking time for outbound operations and affecting the overall outbound efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, equipment, and medium for optimizing the outbound processing of traditional Chinese medicine decoction pieces, in order to solve the technical problem that the picking time in the existing outbound operation is too long, which affects the overall outbound efficiency.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] This invention provides an optimized method for the outbound processing of traditional Chinese medicine decoction pieces, comprising:

[0007] Obtain the quantity information of user orders for Chinese herbal medicine slices, and allocate user orders to the corresponding warehouse areas for picking based on the quantity information. The warehouse areas include full case area and loose case area. When the quantity information is not less than one full case of goods, the user order is allocated to the full case area; otherwise, the user order is allocated to the loose case area.

[0008] Calculate the distances between each element in the full-item area and the loose-item area respectively. The elements include storage compartments and verification stations. The distances between each element include the distance between storage compartments, the distance between storage compartments and verification stations, and the distance between verification stations.

[0009] Based on the distance between each element, and with path constraints and grid constraints as constraints, and with the objective function of minimizing the distance for picking items to be completed by the picking list, shortest path models for picking in both the full-item area and the loose-item area are established. A genetic algorithm is then used to solve for the shortest picking path. Each picking list includes at least one type of goods, and the starting point and ending point of the shortest picking path model are any one of the multiple check stations.

[0010] In one possible design, the area of ​​the loose parts area is [1 / 3, 1 / 2] of the entire warehouse. Each shelf in the loose parts area has 3-4 storage locations. Each storage location has a minimum and maximum inventory limit. When the inventory of a storage location is lower than the minimum inventory, the assembly line system is notified to automatically replenish the stock.

[0011] In one possible design, the racking locations in the whole-item area are all high-bay locations, and goods are loaded and unloaded using electric forklifts.

[0012] In one possible design, calculating the distances between elements in a warehouse of prepared Chinese medicinal herbs includes:

[0013] The formula for calculating the distance between cells in the same column is as follows:

[0014] D(i1,i2)=|C(i1,2)-C(i2,2)|+2d; (1)

[0015] Where D(i1,i2) represents the distance between storage cell i1 and storage cell i2, C(i1,2) represents the longitudinal offset coordinate of storage cell i1, C(i2,2) represents the longitudinal offset coordinate of storage cell i2, A represents the storage cell in column A of a shelf, and d represents the offset amount when the picking personnel walk around the shelf obstacle zigzag.

[0016] The formula for calculating the distance between cells located in the same row but different columns is as follows:

[0017]

[0018] Where C(i1,1) represents the lateral offset coordinate of compartment i1, C(i2,1) represents the lateral offset coordinate of compartment i2, w1 represents the width of each compartment, and b i1 and b i2 These represent the cabinet numbers corresponding to storage compartments i1 and i2 in the shelf, respectively, and A represents the number of storage compartments in each shelf.

[0019] The formula for calculating the distance between cells located in different rows and columns is as follows:

[0020] D(i1,i2)=|C(i1,1)-C(i2,1)|+|C(i1,2)-C(i2,2)|+2d (3).

[0021] In one possible design, calculating the distances between elements in a warehouse of prepared Chinese medicinal herbs includes:

[0022] The distance between the storage compartment and the verification station is calculated using the following formula:

[0023]

[0024] Where C(i,1) and C(i,2) represent the horizontal and vertical offset coordinates of cell i, respectively, and C(j,1) and C(j,2) represent the horizontal and vertical offset coordinates of cell j, respectively.

[0025] In one possible design, calculating the distances between elements in a warehouse of prepared Chinese medicinal herbs includes:

[0026] Calculate the distance between two checkpoints located on the same side of the shelf using the following formula:

[0027]

[0028] Where, x j1 and x j2 Let y represent the x-coordinates of verification station j1 ​​and verification station j2, respectively. j1 and y j2 Let l1 and l2 represent the ordinates of verification stage j1 and verification stage j2 respectively, and let w2 represent the length and width of each verification stage respectively.

[0029] Calculate the distance between the verification stations located on different sides of the shelf using the following formula:

[0030]

[0031] In one possible design, based on the distances between elements, using path constraints and storage unit constraints as constraints, and taking the minimization of the picking distance for completing the picking list as the objective function, shortest path models for picking in both the full-item area and the loose-item area are established, including:

[0032] Based on the distances between each element, the path constraints are constructed as follows:

[0033]

[0034] Where i and j represent any storage compartment and any verification station, respectively;

[0035] Based on the distances between each element, the cell constraints are constructed as follows:

[0036]

[0037] Where N represents the number of cells in a picking list, 0 represents the starting check station, N+1 represents the ending check station, and 1,2,...,N represent the cells passed between the starting and ending check stations.

[0038] Using the minimum distance to complete picking for each picking order as the objective function, shortest path models for picking in both the full-item area and the loose-item area are established as follows:

[0039]

[0040] Where D(i,j) represents the distance between any storage cell and any verification station, x ij This indicates the path taken during the picking process.

[0041] The second aspect provides an optimized device for the outbound processing of traditional Chinese medicine decoction pieces, including:

[0042] The order allocation module is used to obtain the quantity information of user orders for Chinese herbal medicine slices and allocate user orders to the corresponding warehouse areas for picking based on the quantity information. The warehouse areas include full case area and loose case area. When the quantity information is not less than one full case of goods, the user order is allocated to the full case area; otherwise, the user order is allocated to the loose case area.

[0043] The distance calculation module is used to calculate the distance between each element in the complete item area and the loose item area respectively. The elements include storage compartments and verification stations. The distance between each element includes the distance between storage compartments, the distance between storage compartments and verification stations, and the distance between verification stations.

[0044] The path optimization module is used to establish the shortest picking path model for both the full-item area and the loose-item area based on the distance between each element, with path constraints and grid constraints as constraints, and with the objective function of minimizing the distance to complete picking on the picking list. The module then uses a genetic algorithm to solve for the shortest picking path. Each picking list includes at least one type of goods.

[0045] In one possible design, the area of ​​the loose parts area is [1 / 3, 1 / 2] of the entire warehouse. Each shelf in the loose parts area has 3-4 storage locations. Each storage location has a minimum and maximum inventory limit. When the inventory of a storage location is lower than the minimum inventory, the assembly line system is notified to automatically replenish the stock.

[0046] In one possible design, the racking locations in the whole-item area are all high-bay locations, and goods are loaded and unloaded using electric forklifts.

[0047] In one possible design, when calculating the distances between elements in a traditional Chinese medicine decoction pieces warehouse, the distance calculation module is specifically used for:

[0048] The formula for calculating the distance between cells in the same column is as follows:

[0049] D(i1,i2)=|C(i1,2)-C(i2,2)|+2d; (1)

[0050] Where D(i1,i2) represents the distance between storage cell i1 and storage cell i2, C(i1,2) represents the longitudinal offset coordinate of storage cell i1, C(i2,2) represents the longitudinal offset coordinate of storage cell i2, A represents the storage cell in column A of a shelf, and d represents the offset amount when the picking personnel walk around the shelf obstacle zigzag.

[0051] The formula for calculating the distance between cells located in the same row but different columns is as follows:

[0052]

[0053] Where C(i1,1) represents the lateral offset coordinate of compartment i1, C(i2,1) represents the lateral offset coordinate of compartment i2, w1 represents the width of each compartment, and b i1 and b i2 These represent the cabinet numbers corresponding to storage compartments i1 and i2 in the shelf, respectively, and A represents the number of storage compartments in each shelf.

[0054] The formula for calculating the distance between cells located in different rows and columns is as follows:

[0055] D(i1,i2)=|C(i1,1)-C(i2,1)|+|C(i1,2)-C(i2,2)|+2d (3).

[0056] In one possible design, when calculating the distances between elements in a traditional Chinese medicine decoction pieces warehouse, the distance calculation module is specifically used for:

[0057] The distance between the storage compartment and the verification station is calculated using the following formula:

[0058]

[0059] Where C(i,1) and C(i,2) represent the horizontal and vertical offset coordinates of cell i, respectively, and C(j,1) and C(j,2) represent the horizontal and vertical offset coordinates of cell j, respectively.

[0060] In one possible design, when calculating the distances between elements in a traditional Chinese medicine decoction pieces warehouse, the distance calculation module is specifically used for:

[0061] Calculate the distance between two checkpoints located on the same side of the shelf using the following formula:

[0062]

[0063] Where, x j1 and x j2 Let y represent the x-coordinates of verification station j1 ​​and verification station j2, respectively. j1 and y j2 Let l1 and l2 represent the ordinates of verification stage j1 and verification stage j2 respectively, and let w2 represent the length and width of each verification stage respectively.

[0064] Calculate the distance between the verification stations located on different sides of the shelf using the following formula:

[0065]

[0066] In one possible design, based on the distances between elements, using path constraints and storage unit constraints as constraints, and taking the minimization of the picking distance for completing the picking list as the objective function, shortest path models for picking in both the full-item area and the loose-item area are established, including:

[0067] Based on the distances between each element, the path constraints are constructed as follows:

[0068]

[0069] Where i and j represent any storage compartment and any verification station, respectively;

[0070] Based on the distances between each element, the cell constraints are constructed as follows:

[0071]

[0072] Where N represents the number of cells in a picking list, 0 represents the starting check station, N+1 represents the ending check station, and 1,2,...,N represent the cells passed between the starting and ending check stations.

[0073] Using the minimum distance to complete picking for each picking order as the objective function, shortest path models for picking in both the full-item area and the loose-item area are established as follows:

[0074]

[0075] Where D(i,j) represents the distance between any storage cell and any verification station, x ij This indicates the path taken during the picking process.

[0076] A third aspect provides a computer device comprising a memory, a processor, and a transceiver connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the optimized method for the outbound processing of traditional Chinese medicine decoction pieces as described in any possible design of the first aspect.

[0077] The fourth aspect provides a computer-readable storage medium storing instructions that, when executed on a computer, perform the optimized method for the outbound processing of traditional Chinese medicine decoction pieces as described in any possible design of the first aspect.

[0078] Fifthly, the present invention provides a computer program product containing instructions that, when the instructions are executed on a computer, cause the computer to perform the optimized method for the outbound processing of traditional Chinese medicine decoction pieces as described in any possible design of the first aspect.

[0079] The advantages of this invention compared to the prior art are as follows:

[0080] This invention obtains the quantity information from user orders for traditional Chinese medicine (TCM) decoction pieces and allocates these orders to corresponding warehouse areas for picking. When the quantity is not less than one full case, the user order is allocated to the full case area; otherwise, it is allocated to the loose case area. This invention accelerates the outbound process by picking within smaller areas and handles large orders by shipping them in full cases. This adapts to the specific characteristics of TCM decoction piece orders, reduces labor costs, increases outbound efficiency, and provides timely outbound delivery for the customer's pharmaceutical supply chain. By using any check station as the starting or ending point of the shortest path picking model, it overcomes the difficulty of traversal and search caused by uncertain start and end points in existing warehouses with multiple check stations, thereby shortening picking time and improving outbound operation efficiency. Attached Figure Description

[0081] Figure 1 is a flowchart of the optimized method for the release of traditional Chinese medicine decoction pieces in the embodiments of this application. Detailed Implementation

[0082] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0083] Example

[0084] To address the technical problem of excessively long picking times in existing outbound operations, which negatively impact overall outbound efficiency, this application provides an optimized outbound method for traditional Chinese medicine (TCM) decoction pieces. This method obtains the quantity information from user orders for TCM decoction pieces and allocates these orders to corresponding warehouse areas for picking. When the quantity is not less than one full case, the user order is allocated to the full case area; otherwise, it is allocated to the loose case area. In other words, this invention accelerates the outbound process by picking within smaller areas and handles large orders by outbounding them in full cases. This adapts to the specific characteristics of TCM decoction piece orders, reduces labor costs, increases outbound efficiency, and provides timely outbound delivery for the customer's pharmaceutical supply chain. By using any check station as the starting or ending point of the shortest path model for picking, it overcomes the difficulty of traversal and search caused by uncertain start and end points in existing warehouses with multiple check stations, thereby shortening picking time and improving outbound operation efficiency.

[0085] The following will provide a detailed description of the optimized method for the outbound processing of traditional Chinese medicine decoction pieces provided in the embodiments of this application.

[0086] It should be noted that the optimized method for the outbound processing of traditional Chinese medicine decoction pieces provided in this application can be applied to any terminal device using an operating system. The operating system includes, but is not limited to, Windows, Mac, Linux, Chrome OS, UNIX, iOS, and Android systems; these are not limited here. The terminal device includes, but is not limited to, iPads, personal mobile computers, industrial computers, and personal computers; these are not limited here either. For ease of description, unless otherwise specified, the embodiments in this application are described using an industrial computer as the execution subject. It is understood that the execution subject does not constitute a limitation on the embodiments of this application, and other types of terminal devices may be used as the execution subject in some other embodiments.

[0087] Figure 1 shows a flowchart of the optimized method for the release of traditional Chinese medicine decoction pieces provided in this application embodiment. The optimized method for the release of traditional Chinese medicine decoction pieces includes, but is not limited to, steps S1 to S3:

[0088] Step S1. Obtain the quantity information of the user's order for Chinese herbal medicine slices, and allocate the user's order to the corresponding warehouse area for picking according to the quantity information. The warehouse area includes a full case area and a loose case area. When the quantity information is not less than one full case of goods, the user's order is allocated to the full case area; otherwise, the user's order is allocated to the loose case area.

[0089] It should be noted that, in this embodiment, the "full case area" refers to the warehouse area storing full cases of goods, while the "loose case area" refers to the warehouse area storing loose goods. The racks in the full case area are all high-bay racks, and goods are loaded and unloaded using electric forklifts. When a customer purchases a full case of a particular item, the system automatically assigns the order to the full case rack, and designated personnel use electric forklifts to retrieve the full case. The loose case area occupies [1 / 3, 1 / 2] of the entire warehouse. Each rack in the loose case area has 3-4 racks, and each rack has minimum and maximum inventory limits. When the inventory at a rack falls below the minimum limit, the production line system is notified to automatically replenish stock. Of course, manual replenishment is also possible, ensuring that the warehouse inventory remains within a stable range to meet daily loose case outbound needs.

[0090] Step S2. Calculate the distance between each element in the whole item area and the loose item area respectively. The element includes the storage compartment and the verification table. The distance between each element includes the distance between storage compartments, the distance between storage compartments and verification tables, and the distance between verification tables.

[0091] It should be noted that the method described in this application embodiment is mainly applied to large-scale Chinese herbal medicine storage warehouses. For example, a Chinese herbal medicine warehouse consists of multiple parallel horizontal and vertical aisles, each with the same width. Specifically, the warehouse has multiple sets of shelves, each shelf with multiple storage compartments, and multiple verification stations distributed on the same or different sides of the shelves. The specific layout can be adjusted according to actual application needs and is not limited here. A barcode scanning device, such as an RFID reader, is installed at each verification station. The product label can be set as an RFID tag. By installing a barcode scanning device at the verification station, product information can be automatically verified, avoiding errors caused by manual verification. The product information includes, but is not limited to, product ID, manufacturer, product name, specifications, place of origin, batch number, production date, and expiration date.

[0092] Preferably, since there is an offset between the grid coordinates and the picker's coordinates when picking items from the grid, to avoid further complex calculations of the coordinate offset, this embodiment constructs an offset matrix for each grid coordinate before calculating the distance between the grid element and other elements. This converts the grid coordinate values ​​to the position of the center point of the adjacent aisle, i.e., the external offset of the picker's position when retrieving items. This achieves consistency between the grid coordinates and the picker's position offset. For example, when two closely adjacent shelves are in the same row, the formula for calculating the coordinate offset between the left and right shelves is:

[0093]

[0094] Where C(i,1) represents the lateral offset coordinate of compartment i, C(i,2) represents the longitudinal offset coordinate of compartment i, w1 represents the width of each compartment, l1 represents the length of each compartment, and lr represents the longitudinal aisle length.

[0095] Similarly, the formula for calculating the coordinate offset of each verification stage can be obtained as follows:

[0096]

[0097] Where C(j,1) represents the lateral offset coordinate of verification station j, C(j,2) represents the longitudinal offset coordinate of verification station j, w2 represents the width of each verification station, and l2 represents the length of each verification station.

[0098] Based on the above-disclosed content, by calculating the coordinate offset of the shelf and the coordinate offset of each check station, it is possible to unify the coordinates of the storage compartments with the position offset of the picker. By unifying the calculation of the distance between each element under the same coordinate system, complex calculations are avoided.

[0099] In one possible design, calculating the distances between elements in a warehouse of prepared Chinese medicinal herbs includes:

[0100] The formula for calculating the distance between cells in the same column is as follows:

[0101] D(i1,i2)=|C(i1,2)-C(i2,2)|+2d; (1)

[0102] Where D(i1,i2) represents the distance between storage cell i1 and storage cell i2, C(i1,2) represents the longitudinal offset coordinate of storage cell i1, C(i2,2) represents the longitudinal offset coordinate of storage cell i2, A represents the storage cell in column A of a shelf, and d represents the offset amount when the picking personnel walk around the shelf obstacle zigzag.

[0103] The formula for calculating the distance between cells located in the same row but different columns is as follows:

[0104]

[0105] Where C(i1,1) represents the lateral offset coordinate of compartment i1, C(i2,1) represents the lateral offset coordinate of compartment i2, w1 represents the width of each compartment, and b i1 and b i2 These represent the cabinet numbers corresponding to storage compartments i1 and i2 in the shelf, respectively, and A represents the number of storage compartments in each shelf.

[0106] The formula for calculating the distance between cells located in different rows and columns is as follows:

[0107] D(i1,i2)=|C(i1,1)-C(i2,1)|+|C(i1,2)-C(i2,2)|+2d (3).

[0108] In one possible design, calculating the distances between elements in a warehouse of prepared Chinese medicinal herbs includes:

[0109] The distance between the storage compartment and the verification station is calculated using the following formula:

[0110]

[0111] Where C(i,1) and C(i,2) represent the horizontal and vertical offset coordinates of cell i, respectively, and C(j,1) and C(j,2) represent the horizontal and vertical offset coordinates of cell j, respectively.

[0112] In one possible design, calculating the distances between elements in a warehouse of prepared Chinese medicinal herbs includes:

[0113] Calculate the distance between two checkpoints located on the same side of the shelf using the following formula:

[0114]

[0115] Where, x j1 and x j2 Let y represent the x-coordinates of verification station j1 ​​and verification station j2, respectively. j1 and y j2 Let l1 and l2 represent the ordinates of verification stage j1 and verification stage j2 respectively, and let w2 represent the length and width of each verification stage respectively.

[0116] Calculate the distance between the verification stations located on different sides of the shelf using the following formula:

[0117]

[0118] Step S3. Based on the distance between each element, with path constraints and grid constraints as constraints, and with the objective function of minimizing the distance for picking items to be completed by the picking list, establish the shortest picking path models for the full-item area and the loose-item area respectively, and use a genetic algorithm to solve the shortest picking path. Each picking list includes at least one type of goods, and the starting point and ending point of the shortest picking path model are any one of the multiple check stations.

[0119] It's important to note that traditional single-exit and single-checkpoint picking path optimization often involves fixed start and end points. To address this, we've modeled warehouse picking paths based on TSP (Tracking Strategy Programming) and solved the model using algorithms such as simulated annealing, ant colony optimization, and tabu search, achieving relatively ideal picking paths. However, this method is unsuitable for path optimization with multiple checkpoints, as the start and end points are often not fixed. For example, assuming a warehouse has n checkpoints, performing shortest path traversal on all checkpoints results in a complexity of O(n log n) for checkpoint selection alone. 2 Furthermore, the computational efficiency of intelligent optimization algorithms decreases sharply with the increase in the number of check stations. Therefore, this application introduces the concept of replacement check stations, transforming the multi-check station path planning problem with unfixed start and end points into a picking path optimization problem with known start and end points. Based on this, a reasonable allocation strategy for multiple picking orders is provided to minimize the working time of picking personnel. Specifically, this application solves the above problem by introducing fixed check stations. Specifically, if a picking order has N storage compartments Hi = (i = 1, ..., N), and the start and end points can be arbitrarily chosen from all check stations, then to obtain the shortest path, a fixed check station is introduced, minimizing the path between the fixed check station and each storage compartment it passes through. This solves the problem that multi-check station path optimization often involves unfixed start and end points.

[0120] In one possible design of step S3, based on the distance between each element, using path constraints and storage cell constraints as constraints, and taking the minimum distance for completing the picking of the picking list as the objective function, shortest path models for picking in the full-item area and the loose-item area are established respectively, including:

[0121] Based on the distances between each element, the path constraints are constructed as follows:

[0122]

[0123] Where i and j represent any storage compartment and any verification station, respectively;

[0124] Based on the distances between each element, the cell constraints are constructed as follows:

[0125]

[0126] Where N represents the number of cells in a picking list, 0 represents the starting check station, N+1 represents the ending check station, and 1,2,...,N represent the cells passed between the starting and ending check stations.

[0127] Using the minimum distance to complete picking for each picking order as the objective function, shortest path models for picking in both the full-item area and the loose-item area are established as follows:

[0128]

[0129] Where D(i,j) represents the distance between any storage cell and any verification station, x ij This indicates the path taken during the picking process.

[0130] Based on the above disclosure, this application embodiment transforms the calculation of multi-check station path optimization into a picking path optimization problem with known start and end points. This problem is NP-hard, and the genetic algorithm is used to optimize it based on the idea of ​​survival of the fittest in population genetic operations. When solving more complex combinatorial optimization problems, it can usually optimize the results better than conventional optimization algorithms. Therefore, this application embodiment uses a genetic algorithm to solve the path planning strategy. The algorithm principle of the genetic algorithm is an existing algorithm principle, which will not be described in detail here.

[0131] Based on the above disclosure, this application embodiment obtains the quantity information of user orders for traditional Chinese medicine decoction pieces, and allocates user orders to corresponding warehouse areas for picking according to the quantity information. When the quantity information is not less than a whole case of goods, the user order is allocated to the whole case area; otherwise, the user order is allocated to the loose case area. That is, the present invention speeds up the outbound process by picking in small areas and outbounds large purchase orders in whole cases, which can adapt to the special characteristics of traditional Chinese medicine decoction piece orders, reduce labor costs, increase outbound efficiency, and provide outbound timeliness guarantee for the customer's pharmaceutical supply chain. By using any verification station as the starting point or ending point of the picking shortest path model, the problem of traversal search difficulties caused by the uncertainty of the starting and ending points in the case of multiple verification stations in the existing warehouse is overcome, thereby shortening the picking time and improving the efficiency of outbound operations.

[0132] The second aspect provides an optimized device for the outbound processing of traditional Chinese medicine decoction pieces, including:

[0133] The order allocation module is used to obtain the quantity information of user orders for Chinese herbal medicine slices and allocate user orders to the corresponding warehouse areas for picking based on the quantity information. The warehouse areas include full case area and loose case area. When the quantity information is not less than one full case of goods, the user order is allocated to the full case area; otherwise, the user order is allocated to the loose case area.

[0134] The distance calculation module is used to calculate the distance between each element in the complete item area and the loose item area respectively. The elements include storage compartments and verification stations. The distance between each element includes the distance between storage compartments, the distance between storage compartments and verification stations, and the distance between verification stations.

[0135] The path optimization module is used to establish the shortest picking path model for both the full-item area and the loose-item area based on the distance between each element, with path constraints and grid constraints as constraints, and with the objective function of minimizing the distance to complete picking on the picking list. The module then uses a genetic algorithm to solve for the shortest picking path. Each picking list includes at least one type of goods.

[0136] In one possible design, the area of ​​the loose parts area is [1 / 3, 1 / 2] of the entire warehouse. Each shelf in the loose parts area has 3-4 storage locations. Each storage location has a minimum and maximum inventory limit. When the inventory of a storage location is lower than the minimum inventory, the assembly line system is notified to automatically replenish the stock.

[0137] In one possible design, the racking locations in the whole-item area are all high-bay locations, and goods are loaded and unloaded using electric forklifts.

[0138] In one possible design, when calculating the distances between elements in a traditional Chinese medicine decoction pieces warehouse, the distance calculation module is specifically used for:

[0139] The formula for calculating the distance between cells in the same column is as follows:

[0140] D(i1,i2)=|C(i1,2)-C(i2,2)|+2d; (1)

[0141] Where D(i1,i2) represents the distance between storage cell i1 and storage cell i2, C(i1,2) represents the longitudinal offset coordinate of storage cell i1, C(i2,2) represents the longitudinal offset coordinate of storage cell i2, A represents the storage cell in column A of a shelf, and d represents the offset amount when the picking personnel walk around the shelf obstacle zigzag.

[0142] The formula for calculating the distance between cells located in the same row but different columns is as follows:

[0143]

[0144] Where C(i1,1) represents the lateral offset coordinate of compartment i1, C(i2,1) represents the lateral offset coordinate of compartment i2, w1 represents the width of each compartment, and b i1 and b i2 These represent the cabinet numbers corresponding to storage compartments i1 and i2 in the shelf, respectively, and A represents the number of storage compartments in each shelf.

[0145] The formula for calculating the distance between cells located in different rows and columns is as follows:

[0146] D(i1,i2)=|C(i1,1)-C(i2,1)|+|C(i1,2)-C(i2,2)|+2d (3).

[0147] In one possible design, when calculating the distances between elements in a traditional Chinese medicine decoction pieces warehouse, the distance calculation module is specifically used for:

[0148] The distance between the storage compartment and the verification station is calculated using the following formula:

[0149]

[0150] Where C(i,1) and C(i,2) represent the horizontal and vertical offset coordinates of cell i, respectively, and C(j,1) and C(j,2) represent the horizontal and vertical offset coordinates of cell j, respectively.

[0151] In one possible design, when calculating the distances between elements in a traditional Chinese medicine decoction pieces warehouse, the distance calculation module is specifically used for:

[0152] Calculate the distance between two checkpoints located on the same side of the shelf using the following formula:

[0153]

[0154] Where, x j1 and x j2 Let y represent the x-coordinates of verification station j1 ​​and verification station j2, respectively. j1 and y j2 Let l1 and l2 represent the ordinates of verification stage j1 and verification stage j2 respectively, and let w2 represent the length and width of each verification stage respectively.

[0155] Calculate the distance between the verification stations located on different sides of the shelf using the following formula:

[0156]

[0157] In one possible design, based on the distances between elements, using path constraints and storage unit constraints as constraints, and taking the minimization of the picking distance for completing the picking list as the objective function, shortest path models for picking in both the full-item area and the loose-item area are established, including:

[0158] Based on the distances between each element, the path constraints are constructed as follows:

[0159]

[0160] Where i and j represent any storage compartment and any verification station, respectively;

[0161] Based on the distances between each element, the cell constraints are constructed as follows:

[0162]

[0163] Where N represents the number of cells in a picking list, 0 represents the starting check station, N+1 represents the ending check station, and 1,2,...,N represent the cells passed between the starting and ending check stations.

[0164] Using the minimum distance to complete picking for each picking order as the objective function, shortest path models for picking in both the full-item area and the loose-item area are established as follows:

[0165]

[0166] Where D(i,j) represents the distance between any storage cell and any verification station, x ij This indicates the path taken during the picking process.

[0167] The working process, working details and technical effects of the aforementioned device provided in the second aspect of this embodiment can be found in the method described in the first aspect or any possible design of the first aspect, and will not be repeated here.

[0168] Thirdly, the present invention provides a computer device comprising a memory, a processor, and a transceiver connected in sequence and communication, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the optimized method for the outbound processing of traditional Chinese medicine decoction pieces as described in any possible design of the first aspect.

[0169] Specifically, the memory may include, but is not limited to, Random-Access Memory (RAM), Read-Only Memory (ROM), Flash Memory, First-In-First-Out (FIFO) Memory, and / or First-In-Last-Out (FILO) Memory, etc.; the processor may not be limited to the STM32F105 series microprocessor; the transceiver may be, but is not limited to, a WiFi (Wireless Fidelity) wireless transceiver, a Bluetooth wireless transceiver, a GPRS (General Packet Radio Service) wireless transceiver, and / or a ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard) wireless transceiver, etc. Furthermore, the computer device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0170] The working process, working details and technical effects of the aforementioned computer device provided in the third aspect of this embodiment can be found in the method described in the first aspect or any possible design of the first aspect, and will not be repeated here.

[0171] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, perform the optimized method for the outbound processing of traditional Chinese medicine decoction pieces as described in any possible design of the first aspect.

[0172] The computer-readable storage medium refers to a carrier for storing data, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives and / or memory sticks, etc. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0173] The working process, working details and technical effects of the aforementioned computer-readable storage medium provided in the fourth aspect of this embodiment can be found in the method described in the first aspect or any possible design of the first aspect, and will not be repeated here.

[0174] Fifthly, the present invention provides a computer program product containing instructions that, when the instructions are executed on a computer, cause the computer to perform the optimized method for the outbound processing of traditional Chinese medicine decoction pieces as described in any possible design of the first aspect.

[0175] The working process, working details and technical effects of the aforementioned computer program product containing instructions provided in the fifth aspect of this embodiment can be found in the method described in the first aspect or any possible design of the first aspect, and will not be repeated here.

[0176] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An optimized method for the release of traditional Chinese medicine decoction pieces from storage, characterized in that, include: Obtain the quantity information from user orders for Chinese herbal medicine slices, and allocate user orders to corresponding warehouse areas for picking based on the quantity information. The warehouse areas include full-case areas and loose-item areas. When the quantity information is not less than one full case, the user order is allocated to the full-case area; otherwise, the user order is allocated to the loose-item area. Calculate the distances between each element in the full-case area and the loose-item area. Elements include storage compartments and checking stations. The distances between elements include the distance between storage compartments, the distance between a storage compartment and a checking station, and the distance between checking stations. Based on the distances between elements, and using path constraints and grid constraints as constraints, with the objective function being the minimum distance for completing the picking of a picking slip, shortest path models for picking in both the full-case and loose-case areas are established. A genetic algorithm is then used to solve for the shortest picking paths. Each picking slip includes at least one type of goods, and the starting and ending points of the shortest picking path models are any one of multiple checkpoints. The distances between elements in the traditional Chinese medicine decoction pieces warehouse are calculated, including the distances between grids located in the same column, using the following formula: (1) Among them, Indicates the quantity of goods and goods The distance between them Indicates the quantity of goods The vertical offset coordinate, Indicates the quantity of goods The vertical offset coordinate, This represents the offset of a picker walking around a shelf obstacle along a zigzag line; the distance between cells in the same row and different columns is calculated using the following formula: (2) Among them, Indicates the quantity of goods The horizontal offset coordinate, Indicates the quantity of goods The horizontal offset coordinate, This indicates the width of each compartment. and Representing the compartments and goods The corresponding cabinet number on the shelf. This indicates the number of shelves on each shelf; the distance between shelves located in different rows and columns is calculated using the following formula: (3); Calculate the distances between each element in the Chinese herbal medicine warehouse, including: calculating the distance between the storage compartment and the verification table. The calculation formula is as follows: ;in, and Representing the compartments The horizontal and vertical offset coordinates, and Representing the compartments The horizontal and vertical offset coordinates are given, where b1 represents the cabinet number corresponding to storage cell i in the shelf; the distances between elements in the traditional Chinese medicine decoction pieces warehouse are calculated, including: calculating the distance between verification stations on the same side of the shelf, using the following formula: (4) Among them, and These represent the review station. and review table x-coordinate and These represent the review station. and review table The ordinate, and Let represent the length and width of each checking station, respectively; calculate the distance between checking stations located on different sides of the shelf using the following formula: （5）。 2. The method for optimizing the outbound processing of traditional Chinese medicine decoction pieces according to claim 1, characterized in that, The area occupied by the loose parts area is [1 / 3, 1 / 2] of the entire warehouse. Each shelf in the loose parts area has 3-4 layers of storage locations. Each storage location has a minimum and maximum inventory limit. When the inventory of a storage location is lower than the minimum inventory, the assembly line system is notified to automatically replenish the stock.

3. The method for optimizing the outbound processing of traditional Chinese medicine decoction pieces according to claim 1, characterized in that, The shelving in the whole-item area has high-level storage locations, and goods are loaded and unloaded using electric forklifts.

4. The method for optimizing the outbound processing of traditional Chinese medicine decoction pieces according to claim 1, characterized in that, Based on the distances between elements, and using path constraints and storage unit constraints as conditions, with the objective function being to minimize the distance required to complete picking on the picking slip, shortest path models for picking in both the full-item area and the loose-item area are established. This includes: constructing path constraints based on the distances between elements as follows: (6) Among them, Let each element represent an arbitrary storage cell and an arbitrary verification station. Based on the distances between the elements, the storage cell constraints are as follows: (7) Among them, This indicates the number of storage compartments contained in a picking list. Indicates the starting review station. This indicates the termination of the review process. This represents the storage cells traversed between the starting and ending checkpoints. Using the minimum distance for each picking order to complete the picking process as the objective function, shortest path models for picking in both the full-item and loose-item areas are established as follows: (4) Among them, This represents the distance between any storage compartment and any checking station. This indicates the path taken during the picking process.

5. A device for optimizing the release of traditional Chinese medicine decoction pieces, characterized in that, The apparatus is used to implement the method for optimizing the outbound processing of traditional Chinese medicine decoction pieces according to any one of claims 1 to 4, wherein the apparatus includes: an order allocation module, used to obtain the quantity information of user orders for traditional Chinese medicine decoction pieces, and allocate user orders to corresponding warehouse areas for picking according to the quantity information, wherein the warehouse areas include a full-case area and a loose-case area, and when the quantity information is not less than one full-case item, the user order is allocated to the full-case area; otherwise, the user order is allocated to the loose-case area; a distance calculation module, used to calculate the distance between each element in the full-case area and the loose-case area respectively, wherein the elements include storage compartments and verification stations, and the distance between each element includes the distance between storage compartments, the distance between storage compartments and verification stations, and the distance between verification stations; a path optimization module, used to establish the shortest picking path model for the full-case area and the loose-case area respectively, based on the distance between each element, with path constraints and storage compartment constraints as constraints, and with the objective function of minimizing the distance of picking to complete the picking of the picking order, and using a genetic algorithm to solve the shortest picking path, wherein each picking order includes at least one type of goods.

6. A computer device, characterized in that, The device includes a memory, a processor, and a transceiver connected in sequence. The memory is used to store computer programs, the transceiver is used to send and receive messages, and the processor is used to read the computer programs and execute the optimized method for the outbound processing of traditional Chinese medicine decoction pieces as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, perform the optimized method for the release of traditional Chinese medicine decoction pieces as described in any one of claims 1 to 4.

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