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CN-121998541-A - Warehouse layout method, medium, program product and electronic device

CN121998541ACN 121998541 ACN121998541 ACN 121998541ACN-121998541-A

Abstract

The application relates to the field of logistics management, and discloses a warehouse layout method, a medium, a program product and electronic equipment, which can optimize the warehouse layout, improve the warehouse operation efficiency and reduce the warehouse cost. The method comprises the steps of obtaining an order data set in a set time period, determining a plurality of functional areas in a warehouse according to the order data set, determining a first area of each functional area according to the order data set, taking the position of each functional area as a first optimization object, taking the length-width ratio of each functional area as a second optimization object, performing double coding processing on the first optimization object and the second optimization object by using a genetic algorithm based on the first area of each functional area, decoding the coded first optimization object and second optimization object, and determining an optimization result meeting preset conditions, wherein the optimization result comprises the target position of each functional area and the target length-width ratio of each functional area. It will be appreciated that the above-described preset conditions are used to characterize the degree of optimisation of the location and aspect ratio of the functional regions.

Inventors

  • ZHANG XUE

Assignees

  • 株式会社日立制作所

Dates

Publication Date
20260508
Application Date
20241105

Claims (20)

  1. 1. A warehouse layout method, the method comprising: Acquiring an order data set in a set time period; Determining a plurality of functional areas in a warehouse according to the order data set; Determining a first area of each functional area according to the order data set; taking the position of each functional area as a first optimization object, taking the length-width ratio of each functional area as a second optimization object, And based on the first area of each functional area, performing double coding processing on the first optimized object and the second optimized object by utilizing a genetic algorithm, decoding the coded first optimized object and the coded second optimized object, and determining an optimized result meeting preset conditions, wherein the optimized result comprises a target position of each functional area and a target length-width ratio of each functional area.
  2. 2. The method of claim 1, wherein the order data in the set of order data comprises at least one of order number, order date, order time score, type of goods, quantity of goods, process flow, container size, job type, wherein, The job types comprise at least one of ex-warehouse operation, warehouse-in operation and in-warehouse operation, wherein each job type corresponds to a plurality of job flows, and each job flow corresponds to one functional area; the processing flow comprises at least one operation flow corresponding to the operation type.
  3. 3. The method of claim 2, wherein said determining a plurality of functional areas in said warehouse from said order data set comprises: Determining the plurality of functional areas of the warehouse according to the operation flows corresponding to the ex-warehouse operation, the warehouse-in operation and the in-warehouse operation in the order data set; The functional areas comprise at least one of a discharging area, a warehousing temporary storage area, a support removing operation area, a quality inspection operation area, a packaging operation area, a delivery temporary storage area, a support loading/stacking operation area, a loading area, a storage area, a sorting area, an equipment placement area, a defective product/withdrawal area and an office area.
  4. 4. The method of claim 1, wherein said determining a first area of each of said functional areas from said order data set comprises: Determining active balance maximum value of the warehouse entry amount active balance and the warehouse exit amount of the warehouse in the set time period according to the order data set; Determining the maximum area of each functional area according to the active balance maximum value; And determining the corresponding first area according to the maximum area of each functional area, wherein the first area of each functional area is smaller than or equal to the corresponding maximum area.
  5. 5. The method of claim 4, wherein said determining the corresponding first area from the maximum area of each of the functional areas comprises: and taking the maximum area of each functional area as the corresponding first area.
  6. 6. The method of claim 4, wherein said determining the corresponding first area from the maximum area of each of the functional areas comprises: determining a second area of each functional area, wherein the second area is a preset area or an area calculated according to the operation processing capacity of the unit area of the functional area; If the second area of the functional area is smaller than the corresponding maximum area, the second area is taken as the first area of the functional area; And if the second area of the functional area is larger than or equal to the corresponding maximum area, taking the maximum area as the first area of the functional area.
  7. 7. The method of claim 4, wherein determining active balance maximum values for the warehouse entry and exit volume active balance of the warehouse over the predetermined period of time based on the order data set comprises: Rolling and dividing the order data set into a plurality of sub order data sets according to the delay digestion period of the warehouse goods processing; Calculating the warehouse-in cargo amount and the warehouse-out cargo amount active balance in each sub order data set to obtain a plurality of cargo amounts active balance; And taking the maximum value of the cargo amounts active balance as the maximum value of active balance in the preset time period.
  8. 8. The method of claim 1, wherein double encoding the first optimization object and the second optimization object using a genetic algorithm comprises: Encoding the first optimization object, and determining that the encoded first optimization object is a first chromosome, wherein the first chromosome comprises the numbers of the functional areas, and the positions of the functional areas in the warehouse correspond to the insertion sequence of the numbers of the functional areas in the first chromosome; Encoding the second optimized object, and determining that the encoded second optimized object is a second chromosome, wherein the second chromosome comprises an aspect ratio of each functional region, the aspect ratio is in a preset ratio range, and the size of each functional region corresponds to the first area of the functional region and the aspect ratio in the second chromosome; Wherein the first chromosome and the second chromosome form a set of double-coding chromosomes.
  9. 9. The method of claim 8, wherein decoding the encoded first optimization object and the encoded second optimization object to determine an optimization result that satisfies a preset condition comprises: Constructing a kth double-coding chromosome population of a kth iteration process corresponding to the iteration times equal to k, and solving the kth double-coding chromosome population to obtain the fitness of the kth iteration process, wherein k is a positive integer less than or equal to T, the double-coding chromosome population comprises N groups of double-coding chromosomes, and the fitness is related to the distances between different functional areas and the cargo flow between different functional areas; if the kth iteration process meets the preset condition, determining the optimization result according to the kth double-coding chromosome population; If the kth iteration process does not meet the preset condition, updating the iteration times from k to k+1, re-executing the kth double-coding chromosome population for constructing the kth iteration process, and solving the kth double-coding chromosome population to obtain the adaptability of the kth iteration process until the kth iteration process meets the preset condition; The preset conditions comprise at least one of the following conditions that the current iteration number is larger than T, the difference between the fitness of the current iteration process and the fitness of each iteration process in the previous adjacent S iteration processes is smaller than or equal to a set threshold, and the fitness of the current iteration process is larger than or equal to the preset fitness, wherein S is a positive integer.
  10. 10. The method of claim 9, wherein solving the kth double-encoded chromosome population for fitness of the kth iterative process comprises: calculating the fitness of each double-coding chromosome in N groups of double-coding chromosomes of the kth double-coding chromosome population to obtain N fitness; and taking the maximum value in the N fitness as the fitness of the kth iteration process.
  11. 11. The method of claim 10, wherein the calculating of fitness of the double-encoded chromosome comprises: decoding the double-coding chromosome, and solving the decoded double-coding chromosome according to a two-dimensional boxing algorithm to obtain the insertion coordinates of each functional area and first total areas of a plurality of functional areas in the warehouse, wherein the first total areas are areas of outermost wrapping rectangles of the plurality of functional areas; calculating the distance between different functional areas according to the insertion coordinates of each functional area; and calculating the fitness of the double-coding chromosome according to the cargo flow between different functional areas, the distance between different functional areas and the first total area.
  12. 12. The method of claim 11, wherein the distance between different ones of the functional areas is a manhattan distance, or a non-penetrating shortest path distance, or a distance between boundary points of different ones of the functional areas, or a distance between center points of different ones of the functional areas.
  13. 13. The method of claim 11, wherein the calculation procedure of the insertion coordinates of the functional area includes: Inserting rectangles corresponding to the functional regions in a global area plane based on a first direction of a set origin along a first coordinate axis and a second direction of a second coordinate axis according to an insertion sequence and an aspect ratio of the functional regions in the double-coded chromosome and the corresponding first area, so as to obtain insertion coordinates of the functional regions, wherein the size of the functional regions comprises a first direction length of the rectangles corresponding to the functional regions in the first direction and a second direction length of the rectangles corresponding to the second direction, the insertion coordinates of the functional regions comprise a first direction coordinate value on the first coordinate axis and a second direction coordinate value on the second coordinate axis, the first direction coordinate value of the functional regions plus the first direction length of the functional regions are smaller than or equal to a first total length threshold, the first total length threshold is equal to the opening of the area of the global area plane, and the area of the global area plane is a preset multiple of the value of the sum of the first areas corresponding to the functional regions.
  14. 14. The method of claim 9, wherein constructing a kth double-encoded chromosome population for a kth iterative process comprises: constructing the kth double-coding chromosome population of the kth iterative process in a random manner corresponding to k being equal to 1; And (3) carrying out reconstruction operation on double-coded chromosomes in a kth-1 double-coded chromosome population in a kth-1 iteration process corresponding to k being larger than 1 to obtain the kth double-coded chromosome population in the kth iteration process, wherein the reconstruction operation comprises at least one of a selection operation, a crossover operation and a mutation operation.
  15. 15. The method of claim 14, wherein the step of providing the first information comprises, The crossover operation of numbering of the functional regions in different of the double-encoded chromosomes includes: Exchanging positions of a first functional region number and a second functional region number in a first chromosome of one group of double-coded chromosomes with the second functional region number and the first functional region number of a first chromosome in another group of double-coded chromosomes respectively to obtain two groups of double-coded chromosomes after cross operation; The crossover operation of aspect ratios of the functional regions in different of the double-encoded chromosomes includes: Performing linear processing on the aspect ratio of the functional region corresponding to the first index in the second chromosome of one group of double-coded chromosomes and the aspect ratio q2 of the functional region corresponding to the first index in the second chromosome of the other group of double-coded chromosomes, so that the aspect ratio q1 is adjusted to d1 after the crossover operation, the aspect ratio q2 is adjusted to d2 after the crossover operation, Where d1=α·q1+ (1- α) ·q2, d2= (1- α) ·q1+α·q2, and α is a coefficient smaller than 1.
  16. 16. The method of claim 14, wherein the manipulation of the numbering of the functional regions in different of the double-coded chromosomes comprises: exchanging the third functional region number with the fourth functional region number in a double-coding chromosome; The operation of mutation of the aspect ratio of the functional regions in different of the double-coding chromosomes includes: In a double-coding chromosome, the aspect ratio of the functional region corresponding to the second index is replaced by a numerical value in the range of the preset ratio.
  17. 17. The method of claim 14, wherein the method further comprises: Calculating the acceptance probability of the double-coding chromosome after the crossover operation in the kth double-coding chromosome population; The acceptance probability corresponding to the double-encoded chromosome is a first value, the double-encoded chromosome being taken as one double-encoded chromosome in the kth double-encoded chromosome population; the acceptance probability corresponding to the double-encoded chromosome is not the first value, and the double-encoded chromosome is rolled back to be used as one double-encoded chromosome in the kth double-encoded chromosome population after the crossover operation; Wherein the acceptance probability is related to a maximum value of fitness of each double-coded chromosome of the 1 st double-coded chromosome population in the 1 st iteration process, a minimum value of fitness of each double-coded chromosome of the 1 st double-coded chromosome population in the 1 st iteration process, a fitness of a c-th double-coded chromosome in the k-th double-coded chromosome population in the k-th iteration process, and a maximum fitness of each iteration process, and the acceptance probability decreases with increasing iteration times of the double-coded chromosomes, c is a positive integer less than or equal to N.
  18. 18. A readable medium having stored thereon instructions that, when executed on an electronic device, cause the electronic device to perform the warehouse layout method of any of claims 1-17.
  19. 19. A computer program product, characterized in that the computer program product, when run on an electronic device, causes the electronic device to implement the warehouse layout method of any one of claims 1 to 17.
  20. 20. An electronic device comprising a memory for storing instructions for execution by one or more processors of the electronic device, and the processor being one of the processors of the electronic device for performing the warehouse layout method of any of claims 1-17.

Description

Warehouse layout method, medium, program product and electronic device Technical Field The present application relates to the field of logistics management technologies, and in particular, to a warehouse layout method, a medium, a program product, and an electronic device. Background Currently, the demand for comprehensive logistics storage for production, sales and after-sales has been increasing in an explosive manner. The comprehensive operations of multi-product, small batch, high-frequency cargo quantity, warehouse-in and warehouse-out, detection, processing, sorting, packing and the like have higher requirements for warehouse management. The continuously changing cargo demand promotes the growth of the non-fixed storage space demand. For example, a warehouse with a smaller area is required to reduce warehouse cost when the demand for the amount of goods is small, and a warehouse with a larger area is required when the demand for the amount of goods is large. As another example, to improve work efficiency, such as reducing cargo handling distance, it may be desirable to have some functional areas closer together. Then, with the continuous change of warehouse requirements, how to flexibly adjust the layout of the warehouse becomes a problem to be solved. Disclosure of Invention The embodiment of the application provides a warehouse layout method, a medium, a program product and electronic equipment, which can optimize the warehouse layout, improve the warehouse operation efficiency and reduce the warehouse cost. In a first aspect, an embodiment of the present application provides a warehouse layout method, including acquiring an order data set in a set period of time, determining a plurality of functional areas in a warehouse according to the order data set, determining a first area of each functional area according to the order data set, using a position of each functional area as a first optimization object, using an aspect ratio of each functional area as a second optimization object, performing double coding processing on the first optimization object and the second optimization object by using a genetic algorithm based on the first area of each functional area, decoding the coded first optimization object and second optimization object, and determining an optimization result satisfying a preset condition, where the optimization result includes a target position of each functional area and a target aspect ratio of each functional area. It can be understood that the above preset conditions are used to represent the optimization degree of the position and the aspect ratio of each functional area, and the optimization degree of the target position and the target aspect ratio of each functional area in the optimization result when the preset conditions are satisfied is higher. The order data set in the set time period can reflect the actual demands of the warehouse, and the position and the size of each functional area can be optimized simultaneously by adopting a genetic algorithm based on the order data set. Therefore, the method can automatically optimize the size of each functional area and the layout of the optimized position of the warehouse according to the set order data, thereby being beneficial to achieving the purposes of reducing the total warehouse cost and/or reducing the total occupied area of the warehouse. In one possible implementation manner of the first aspect, the order data in the order data set includes at least one of order serial number, order date, order time division, goods type, goods quantity, processing procedure, container specification and job type, wherein the job type includes at least one of ex-warehouse job, in-warehouse job and in-warehouse job, each job type corresponds to a plurality of job procedures, each job procedure corresponds to a functional area, and the processing procedure includes at least one job procedure corresponding to one job type. For example, the order data set may be historical data of a warehouse existing in a user such as a logistics company or a merchant, or expected data set by the user according to actual warehouse requirements. In one possible implementation manner of the first aspect, determining a plurality of functional areas in the warehouse according to the order data set includes determining a plurality of functional areas of the warehouse according to operation flows corresponding to the ex-warehouse operation, the in-warehouse operation and the in-warehouse operation in the order data set, wherein the plurality of functional areas include at least one of a discharging area, a warehouse-in temporary storage area, a tray disassembling operation area, a quality inspection operation area, a packaging operation area, an ex-warehouse temporary storage area, a loading/stacking operation area, a loading area, a storage area, a sorting area, an equipment placement area, a defective product/returning area and an office area. As an example, i