BPM-based inventory optimization method and system applied to warehouse management system

Abstract

The invention relates to the technical field of data processing, in particular to a BPM-based inventory optimization method and system applied to a warehouse management system, and the method comprises the steps: carrying out the numerical analysis of the real inventory number data of warehouse products and a safe inventory number threshold value, and generating the real inventory number data of target warehouse products; according to the historical sales volume data of the target warehouse product and the sales volume change proportion data of the target warehouse product, performing sales volume estimation, generating real-time sales volume estimation data of the target warehouse product, and calculating real-time demand data of the target warehouse product in combination with the real stock quantity data of the target warehouse product; and performing search processing on the target warehouse product real-time demand quantity data and the established different-condition warehouse product inventory optimization scheme data to generate target warehouse product real-time inventory optimization scheme data, finally constructing target warehouse product inventory optimization data, and pushing the target warehouse product inventory optimization data to a warehouse product inventory optimization platform. The accurate matching of the warehouse product inventory optimization scheme and the scientific optimization of the warehouse inventory are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an inventory optimization method and system based on BPM applied to a warehouse management system. Background Art

[0002] In today's logistics and warehousing industry, the rational management of warehouse inventory plays an important role in the entire operation process. Existing warehouse inventory management technologies often lack dynamic inventory optimization means and cannot match reasonable inventory optimization strategies according to current conditions, resulting in the inability of the industrial chain to operate rationally.

[0003] The Chinese invention patent with publication number CN109740793B introduces an inventory optimization method based on probabilistic demand distribution. The method collects multi-dimensional data such as product inventory balance, in-and-out warehouse details, sales orders, and procurement lead time through an enterprise information management platform; obtains the demand probability density function by statistically analyzing the historical outbound frequency distribution, and establishes a functional relationship between the probability value and the demand forecast value; determines the target satisfaction rate, traverses the probability value according to the demand forecast value, and calculates the simulated satisfaction rate. When the simulated satisfaction rate is greater than or equal to the target satisfaction rate, the method outputs the optimal probability and the corresponding demand forecast value, and maximizes the inventory optimization benefits while ensuring the satisfaction rate. However, the extreme situations of too much inventory and too little inventory are not considered during inventory optimization, resulting in inaccurate inventory analysis results and increasing the amount of calculation in the inventory analysis process. Summary of the invention

[0004] 1. Technical issues to be resolved In order to solve the deficiencies in the background technology, the present invention provides an inventory optimization method and system based on BPM applied to a warehouse management system, so as to achieve accurate matching of warehouse product inventory optimization solutions and scientific optimization of warehouse inventory.

[0005] (II) Technical solution A BPM-based inventory optimization method for a warehouse management system includes the following steps: S1. Collect the actual inventory quantity data of warehouse products; S2. Setting a safety stock quantity threshold, performing numerical analysis on the real stock quantity data of the warehouse products and the stock quantity threshold, and generating the real stock quantity data of the target warehouse products; S3, collecting historical sales data of target warehouse products and sales change ratio data of target warehouse products; S4, performing sales estimation processing on the target warehouse product according to the historical sales data of the target warehouse product and the sales change ratio data of the target warehouse product, and generating real-time sales estimation data on the target warehouse product; S5. Calculate the real-time demand data of the target warehouse product according to the real-time sales volume estimation data of the target warehouse product and the actual inventory quantity data of the target warehouse product; S6. Establish inventory optimization solution data for warehouse products under different situations, perform real-time inventory optimization solution search processing on the inventory optimization solution data for warehouse products under different situations and the real-time demand data of the target warehouse products, and generate real-time inventory optimization solution data for the target warehouse products; S7. Build target warehouse product inventory optimization data based on the target warehouse product real-time demand data and the target warehouse product real-time inventory optimization solution data, and push it to the warehouse product inventory optimization platform.

[0006] The present invention performs numerical analysis on the real inventory quantity data of the warehouse products and the set safety inventory quantity threshold, generates the real inventory quantity data of the target warehouse products, estimates the sales volume of the target warehouse products according to the historical sales volume data of the target warehouse products and the sales volume change ratio data of the target warehouse products, generates real-time sales volume estimation data of the target warehouse products, calculates the real-time demand data of the target warehouse products in combination with the real inventory quantity data of the target warehouse products, performs real-time inventory optimization solution search and processing on the real-time demand data of the target warehouse products and the established warehouse product inventory optimization solution data for different situations, generates real-time inventory optimization solution data of the target warehouse products, finally constructs the inventory optimization data of the target warehouse products, and pushes it to the warehouse product inventory optimization platform, so as to realize the accurate matching of the warehouse product inventory optimization solution and the scientific optimization of the warehouse inventory.

[0007] Preferably, the specific steps for collecting the actual inventory quantity data of warehouse products are as follows: S11. Collect product return rate data of various warehouse products through the warehouse product inventory optimization platform to generate a warehouse product return rate data set ,in, Indicates Product return rate data for warehouse-like products; S12. Collect the real-time inventory quantity of various warehouse products, the inbound quantity of confirmed inbound orders, and the outbound quantity of confirmed outbound orders online through the warehouse product inventory optimization platform, and calculate the real inventory quantity data of various warehouse products in combination with the return rate data of each warehouse product in the warehouse product return rate data set to generate the warehouse product real inventory quantity data set ,in, Indicates The actual inventory quantity data of warehouse-like products; the calculation formula is as follows: , in, , as well as They represent the first The real-time inventory quantity of warehouse-like products, the inbound quantity of confirmed inbound orders, and the outbound quantity of confirmed outbound orders.

[0008] Preferably, the specific steps of setting a safety stock quantity threshold, performing numerical analysis on the real stock quantity data of the warehouse products and the stock quantity threshold, and generating normal real stock quantity data of the warehouse products are as follows: S21. Set the first safety stock quantity threshold to And the second safety stock quantity threshold is ; S22: compare the actual inventory quantity data of each warehouse product in the warehouse product actual inventory quantity data set with the first safety inventory quantity threshold value in sequence. And the second safety stock quantity threshold Perform numerical comparison processing and generate the target warehouse product real inventory quantity data set based on the numerical comparison results ,in, Indicates The actual inventory quantity data corresponding to the warehouse products in normal state; S221, select the first The actual inventory quantity data of the warehouse products and the first safety stock quantity threshold And the second safety stock quantity threshold Perform numerical comparison processing; like , then it means The actual inventory quantity of warehouse products is out of stock. The warehouse product inventory optimization platform sends emergency replenishment instructions to the supply side to perform warehouse product inventory optimization operations. like , then it means The actual inventory quantity of warehouse-like products is in normal state and no operation is performed; like , then it means The actual inventory quantity of this type of warehouse products is in excess. The warehouse product inventory optimization platform is used to cancel the first All unconfirmed incoming orders for warehouse products of this type will be closed, and replenishment operations for such warehouse products will be suspended to optimize warehouse product inventory; S222. Repeat the steps in S221 until all the real inventory quantity data of the warehouse products in the real inventory quantity data set of the warehouse products are traversed, filter out the real inventory quantity data corresponding to all warehouse products in normal status and perform data identification to generate the real inventory quantity data set of the target warehouse products.

[0009] By obtaining the return rate, real-time inventory quantity, incoming quantity of confirmed incoming orders, and outgoing quantity of confirmed outgoing orders of various warehouse products, the real inventory of various warehouse products can be accurately calculated, and numerical analysis can be performed with the set safety inventory quantity threshold to scientifically identify the inventory status of various warehouse products. When warehouse products are out of stock, emergency replenishment is carried out; when warehouse products are in surplus, incoming orders are canceled and replenishment operations are suspended; when warehouse products are in normal status, further analysis is carried out; corresponding processing methods are selected according to different inventory statuses to achieve accurate optimization of warehouse product inventory and effectively avoid unnecessary resource consumption.

[0010] Preferably, the specific steps of collecting the historical sales data of the target warehouse products and the sales change ratio data of the target warehouse products are as follows: S31. Collect the historical sales data of the warehouse products corresponding to the real inventory quantity data of each target warehouse product in the real inventory quantity data set of the target warehouse products online through the warehouse product inventory optimization platform in the previous sales cycle to generate a historical sales data set of the target warehouse products. ,in, Indicates The historical sales data of the warehouse products in normal condition in the previous sales cycle; S32. Collect online, through the warehouse product inventory optimization platform, the sales volume change ratio data of the warehouse products corresponding to the real inventory quantity data of each target warehouse product in the real inventory quantity data set of the target warehouse products in the previous sales cycle, and generate a sales volume change ratio data set of the target warehouse products. ,in, Indicates The sales volume change ratio data of the warehouse products in normal status in the previous sales cycle.

[0011] Preferably, the specific steps of performing target warehouse product sales estimation processing based on the target warehouse product historical sales data and the target warehouse product sales fluctuation data to generate the target warehouse product real-time sales estimation data are as follows: S41: performing target warehouse product sales estimation processing based on the target warehouse product historical sales data in the target warehouse product historical sales data set and the target warehouse product sales fluctuation data in the target warehouse product sales fluctuation data set to generate a target warehouse product real-time sales estimation data set. ,in, Indicates The estimated sales volume of the warehouse products in normal condition in the next sales cycle, and .

[0012] Preferably, the specific steps of calculating the real-time demand data of the target warehouse product according to the real-time sales volume estimation data of the target warehouse product and the actual inventory quantity data of the target warehouse product are as follows: S51, calculating the demand data of various warehouse products in normal state in the next sales cycle according to the real-time sales volume estimation data of the target warehouse products in the real-time sales volume estimation data set and the real inventory quantity data of the target warehouse products in the real inventory quantity data set of the target warehouse products, and generating the real-time demand quantity data set of the target warehouse products ,in, Indicates The demand data of the warehouse products in normal state in the next sales cycle, and .

[0013] The sales volume in the next sales cycle is scientifically estimated through the historical sales data and sales volume change ratio data of the target warehouse products in the previous sales cycle, and the demand for the target warehouse products in the next sales cycle is calculated in combination with the actual inventory quantity data of the target warehouse products, thus ensuring the accuracy of the calculation results and providing a reliable data basis for subsequent operations.

[0014] Preferably, the inventory optimization solution data of warehouse products under different situations are established, and the inventory optimization solution data of warehouse products under different situations and the real-time demand data of the target warehouse products are subjected to real-time inventory optimization solution search processing. The specific steps of generating the real-time inventory optimization solution data of the target warehouse products are as follows: S61. Establish a data set of warehouse product inventory optimization solutions for different situations ,in, Indicates warehouse product inventory optimization plan data for different situations, Indicates the total number of warehouse product inventory optimization solution data under different situations, wherein the warehouse product inventory optimization solution data under different situations includes but is not limited to the number of supplies, supply time points, and supply quantities in the next sales cycle when facing different supply demands; S62: using the moth-to-flame optimization algorithm, the real-time demand data of each target warehouse product in the real-time demand data set of the target warehouse product and the inventory optimization solution data set of warehouse products in different situations are sequentially searched for real-time inventory optimization solution data, and the inventory optimization solution data of warehouse products in different situations that match the real-time demand data of each target warehouse product in the real-time demand data set of the target warehouse product are searched out and the data are marked, so as to generate the real-time inventory optimization solution data set of the target warehouse product. ,in, Indicates Real-time inventory optimization solution data corresponding to warehouse products in normal status; The real-time inventory optimization solution search process includes the following steps: S621. Construct an inventory optimization scheme to search for moth populations, and set the scale of the inventory optimization scheme to search for moth populations. , the current number of iterations is The maximum number of iterations is And the data search space dimension of warehouse product inventory optimization solutions in different situations is ; The warehouse product inventory optimization solution data set under different situations is used as the warehouse product inventory optimization solution data search space under different situations, and randomly generates Each of the warehouse product inventory optimization solution data under different conditions is used as an inventory optimization solution search flame individual, and each inventory optimization solution search moth individual in the inventory optimization solution search moth population is assigned an inventory optimization solution search flame individual; S622, calculating the fitness value of the inventory optimization scheme search flame individual corresponding to each inventory optimization scheme search moth individual, sorting the inventory optimization scheme search flame individuals corresponding to each inventory optimization scheme search moth individual from large to small according to the fitness value, and selecting the inventory optimization scheme search flame individual with the highest fitness value as the current optimal individual; the fitness value calculation formula is as follows: , in, Indicates The fitness value of the inventory optimization scheme searching for moth individuals corresponding to the inventory optimization scheme searching for flame individuals, Indicates The actual inventory quantity of warehouse products after each delivery in the warehouse product inventory optimization plan data of different situations corresponding to each flame individual is searched for by inventory optimization plan. Indicates Search the supply times in the warehouse product inventory optimization plan data for different situations corresponding to each flame individual. Indicates the standard inventory quantity of the warehouse product corresponding to the real-time demand data of the target warehouse product currently being searched for real-time inventory optimization solutions. Indicates the correction value; S623, dynamically update the number of flame individuals searched by the inventory optimization scheme through the number of iterations, and discard the flame individuals searched by the inventory optimization scheme with lower fitness values; the update formula is as follows: , in, Indicates The number of flame individuals searched by the inventory optimization scheme during the iteration, Represents a function that performs a rounding operation according to the rounding principle; S624, each individual in the inventory optimization scheme search moth population will adopt a logarithmic spiral motion strategy in the warehouse product inventory optimization scheme data search space under different conditions to move around the corresponding individual flame to update the position; the position update formula is as follows: , in, Indicates that the inventory optimization scheme searches for the first The inventory optimization scheme searches for the position of the moth individual after the position update, Indicates The distance between a moth individual and its corresponding flame individual, It represents the logarithmic spiral curve parameters that define the movement of the moth individuals to the flame individuals. represents a random number that is uniformly distributed between [-1,1]. Indicates The inventory optimization scheme searches for the location of the flame individuals corresponding to the inventory optimization scheme searching for the moth individuals; S625, calculating the fitness value of each inventory optimization scheme searching moth individual in the inventory optimization scheme searching moth population after the position is updated, if the fitness value of the inventory optimization scheme searching moth individual after the position is updated is greater than the fitness value of the inventory optimization scheme searching flame individual corresponding to the inventory optimization scheme searching moth individual, then updating the position of the inventory optimization scheme searching flame individual corresponding to the inventory optimization scheme searching moth individual to the position after the position is updated; otherwise, retaining the position of the inventory optimization scheme searching flame individual corresponding to the inventory optimization scheme searching moth individual; Re-sort the flame search individuals of the inventory optimization scheme corresponding to the moth search individuals of the inventory optimization scheme from large to small according to the fitness value, and select the flame search individual of the inventory optimization scheme with the highest fitness value as the new current optimal individual; S626, determine the current number of iterations Is it less than the maximum number of iterations? , if the current number of iterations Less than the maximum number of iterations , then the current number of iterations Add 1 and return to S623; otherwise, take the current optimal individual as the global optimal solution, and retain the warehouse product inventory optimization solution data for different situations corresponding to the global optimal solution; S627. Repeat steps S621 to S626 until all the target warehouse product real-time demand data in the target warehouse product real-time demand data set are traversed, and all retained warehouse product inventory optimization plan data for different situations are data-identified to generate a target warehouse product real-time inventory optimization plan data set.

[0015] The moth-to-flame optimization algorithm is used to accurately search for inventory optimization plan data for warehouse products in different situations that match the real-time demand data for the target warehouse products, thereby achieving scientific matching of inventory optimization plans and improving the speed and efficiency of the search process. At the same time, the moth-to-flame optimization algorithm has good robustness, which effectively avoids the search process from being affected by noise in the data, ensures the stability of the search process, and ensures the accuracy of the search results.

[0016] Preferably, the specific steps of constructing the target warehouse product inventory optimization data based on the target warehouse product real-time demand data and the target warehouse product real-time inventory optimization solution data, and pushing it to the warehouse product inventory optimization platform are as follows: S71: The target warehouse product real-time demand data set and the target warehouse product real-time inventory optimization solution dataset Combine data to build product inventory optimization data for target warehouses ; S72: transmitting the target warehouse product inventory optimization data via a wireless communication network Push to the warehouse product inventory optimization platform and execute warehouse product inventory optimization operations.

[0017] The present invention also discloses an inventory optimization system based on BPM applied to a warehouse management system, including a warehouse product real inventory quantity data collection module, a warehouse product screening module, a target warehouse product sales volume estimation module, a target warehouse product real-time demand quantity calculation module, a target warehouse product real-time inventory optimization solution search module, and a target warehouse product inventory optimization data construction module; The warehouse product real inventory quantity data collection module collects product return rate data, real-time inventory quantity, inbound quantity of confirmed inbound orders, and outbound quantity of confirmed outbound orders of various warehouse products through the warehouse product inventory optimization platform, and calculates the real inventory quantity data of various warehouse products to generate the real inventory quantity data of warehouse products; The warehouse product screening module performs numerical comparison processing on the real inventory quantity data of the warehouse product and the set safety inventory quantity threshold, and generates the real inventory quantity data of the target warehouse product according to the numerical comparison result; The target warehouse product sales volume estimation module performs target warehouse product sales volume estimation processing based on the collected target warehouse product historical sales volume data and target warehouse product sales volume fluctuation data, and generates target warehouse product real-time sales volume estimation data; The target warehouse product real-time demand quantity calculation module calculates the demand quantity data of various warehouse products in normal state in the next sales cycle according to the real-time sales volume estimation data of the target warehouse product and the actual inventory quantity data of the target warehouse product, and generates the real-time demand quantity data of the target warehouse product; The target warehouse product real-time inventory optimization solution search module performs real-time inventory optimization solution search processing on the target warehouse product real-time demand data and the established warehouse product inventory optimization solution data for different situations through a moth-to-flame optimization algorithm, searches for the warehouse product inventory optimization solution data for different situations that matches the target warehouse product real-time demand data, performs data identification, and generates the target warehouse product real-time inventory optimization solution data; The target warehouse product inventory optimization data construction module constructs the target warehouse product inventory optimization data by combining the target warehouse product real-time demand data set and the target warehouse product real-time inventory optimization solution data set, pushes it to the warehouse product inventory optimization platform through the wireless communication network, and executes the warehouse product inventory optimization operation.

[0018] (III) Beneficial effects 1. The present invention performs numerical analysis on the real inventory quantity data of the warehouse products and the set safety inventory quantity threshold to generate the real inventory quantity data of the target warehouse products, estimates the sales volume of the target warehouse products according to the historical sales volume data of the target warehouse products and the sales volume change ratio data of the target warehouse products, generates the real-time sales volume estimation data of the target warehouse products, and calculates the real-time demand volume data of the target warehouse products in combination with the real inventory quantity data of the target warehouse products, performs real-time inventory optimization solution search processing on the real-time demand volume data of the target warehouse products and the established warehouse product inventory optimization solution data for different situations, generates the real-time inventory optimization solution data of the target warehouse products, and finally constructs the target warehouse product inventory optimization data, and pushes it to the warehouse product inventory optimization platform, so as to realize the accurate matching of the warehouse product inventory optimization solution and the scientific optimization of the warehouse inventory; 2. By obtaining the return rate, real-time inventory quantity, inbound quantity of confirmed inbound orders, and outbound quantity of confirmed outbound orders of various warehouse products, the real inventory of various warehouse products can be accurately calculated, and numerical analysis can be performed with the set safety inventory quantity threshold to scientifically identify the inventory status of various warehouse products. When the warehouse product is out of stock, emergency replenishment is carried out; when the warehouse product is in surplus, the inbound order is canceled and the replenishment operation is suspended; when the warehouse product is in normal status, further analysis is carried out; according to different inventory status, the corresponding processing method is selected to achieve accurate optimization of warehouse product inventory and effectively avoid unnecessary resource consumption; 3. Scientifically estimate the sales volume in the next sales cycle through the historical sales data and sales volume change ratio data of the target warehouse product in the previous sales cycle, and calculate the demand volume of the target warehouse product in the next sales cycle in combination with the actual inventory quantity data of the target warehouse product, thus ensuring the accuracy of the calculation results and providing a reliable data basis for subsequent operations; 4. The moth-to-flame optimization algorithm is used to accurately search for inventory optimization plan data for warehouse products in different situations that match the real-time demand data of the target warehouse products, thereby achieving scientific matching of inventory optimization plans and improving the speed and efficiency of the search process. At the same time, the moth-to-flame optimization algorithm has good robustness, which effectively avoids the search process from being affected by noise in the data, ensures the stability of the search process, and ensures the accuracy of the search results. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, they can also obtain drawings based on these drawings without paying creative work.

[0020] Figure 1 A flowchart of an inventory optimization method based on BPM applied to a warehouse management system provided by the present invention; Figure 2 A module schematic diagram of a BPM-based inventory optimization system applied to a warehouse management system provided by the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] In the description of the present invention, it is necessary to understand that the terms "opening", "upper", "lower", "top", "middle", "inside" and the like indicating orientation or positional relationship are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the components or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the invention.

[0023] Embodiment 1 is as follows: See also Figure 1 , an inventory optimization method based on BPM applied to a warehouse management system, comprising the following steps: S1. Collect the actual inventory quantity data of warehouse products; S11. Collect product return rate data of various warehouse products through the warehouse product inventory optimization platform to generate a warehouse product return rate data set ,in, Indicates Product return rate data for warehouse-like products; S12. Collect the real-time inventory quantity of various warehouse products, the inbound quantity of confirmed inbound orders, and the outbound quantity of confirmed outbound orders online through the warehouse product inventory optimization platform, and calculate the real inventory quantity data of various warehouse products in combination with the return rate data of each warehouse product in the warehouse product return rate data set to generate the warehouse product real inventory quantity data set ,in, Indicates The actual inventory quantity data of warehouse-like products; the calculation formula is as follows: , in, , as well as They represent the first The real-time inventory quantity of warehouse-like products, the inbound quantity of confirmed inbound orders, and the outbound quantity of confirmed outbound orders.

[0024] S2. Setting a safety stock quantity threshold, performing numerical analysis on the real stock quantity data of the warehouse products and the stock quantity threshold, and generating the real stock quantity data of the target warehouse products; S21. Set the first safety stock quantity threshold to And the second safety stock quantity threshold is ; S22: compare the actual inventory quantity data of each warehouse product in the warehouse product actual inventory quantity data set with the first safety inventory quantity threshold value in sequence. And the second safety stock quantity threshold Perform numerical comparison processing and generate the target warehouse product real inventory quantity data set based on the numerical comparison results ,in, Indicates The actual inventory quantity data corresponding to the warehouse products in normal state; S221, select the first The actual inventory quantity data of the warehouse products and the first safety stock quantity threshold And the second safety stock quantity threshold Perform numerical comparison processing; like , then it means The actual inventory quantity of warehouse products is out of stock. The warehouse product inventory optimization platform sends emergency replenishment instructions to the supply side to perform warehouse product inventory optimization operations. like , then it means The actual inventory quantity of warehouse-like products is in normal state and no operation is performed; like , then it means The actual inventory quantity of this type of warehouse products is in excess. The warehouse product inventory optimization platform is used to cancel the first All unconfirmed incoming orders for warehouse products of this type will be closed, and replenishment operations for such warehouse products will be suspended to optimize warehouse product inventory; S222. Repeat the steps in S221 until all the real inventory quantity data of the warehouse products in the real inventory quantity data set of the warehouse products are traversed, filter out the real inventory quantity data corresponding to all warehouse products in normal status and perform data identification to generate the real inventory quantity data set of the target warehouse products.

[0025] S3, collecting historical sales data of target warehouse products and sales change ratio data of target warehouse products; S31. Collect the historical sales data of the warehouse products corresponding to the real inventory quantity data of each target warehouse product in the real inventory quantity data set of the target warehouse products online through the warehouse product inventory optimization platform in the previous sales cycle to generate a historical sales data set of the target warehouse products. ,in, Indicates The historical sales data of the warehouse products in normal condition in the previous sales cycle; S32. Collect online, through the warehouse product inventory optimization platform, the sales volume change ratio data of the warehouse products corresponding to the real inventory quantity data of each target warehouse product in the real inventory quantity data set of the target warehouse products in the previous sales cycle, and generate a sales volume change ratio data set of the target warehouse products. ,in, Indicates The sales volume change ratio data of the warehouse products in normal status in the previous sales cycle.

[0026] S4, performing sales estimation processing on the target warehouse product according to the historical sales data of the target warehouse product and the sales change ratio data of the target warehouse product, and generating real-time sales estimation data on the target warehouse product; S41: performing target warehouse product sales estimation processing based on the target warehouse product historical sales data in the target warehouse product historical sales data set and the target warehouse product sales fluctuation data in the target warehouse product sales fluctuation data set to generate a target warehouse product real-time sales estimation data set. ,in, Indicates The estimated sales volume of the warehouse products in normal condition in the next sales cycle, and .

[0027] S5. Calculate the real-time demand data of the target warehouse product according to the real-time sales volume estimation data of the target warehouse product and the actual inventory quantity data of the target warehouse product; S51, calculating the demand data of various warehouse products in normal state in the next sales cycle according to the real-time sales volume estimation data of the target warehouse products in the real-time sales volume estimation data set and the real inventory quantity data of the target warehouse products in the real inventory quantity data set of the target warehouse products, and generating the real-time demand quantity data set of the target warehouse products ,in, Indicates The demand data of the warehouse products in normal state in the next sales cycle, and .

[0028] S6. Establish inventory optimization solution data for warehouse products under different situations, perform real-time inventory optimization solution search processing on the inventory optimization solution data for warehouse products under different situations and the real-time demand data of the target warehouse products, and generate real-time inventory optimization solution data for the target warehouse products; S61. Establish a data set of warehouse product inventory optimization solutions for different situations ,in, Indicates warehouse product inventory optimization plan data for different situations, Indicates the total number of warehouse product inventory optimization solution data under different situations, wherein the warehouse product inventory optimization solution data under different situations includes but is not limited to the number of supplies, supply time points, and supply quantities in the next sales cycle when facing different supply demands; S62: using the moth-to-flame optimization algorithm, the real-time demand data of each target warehouse product in the real-time demand data set of the target warehouse product and the inventory optimization solution data set of warehouse products in different situations are sequentially searched for real-time inventory optimization solution data, and the inventory optimization solution data of warehouse products in different situations that match the real-time demand data of each target warehouse product in the real-time demand data set of the target warehouse product are searched out and the data are marked, so as to generate the real-time inventory optimization solution data set of the target warehouse product. ,in, Indicates Real-time inventory optimization solution data corresponding to warehouse products in normal status; The real-time inventory optimization solution search process includes the following steps: S621. Construct an inventory optimization scheme to search for moth populations, and set the scale of the inventory optimization scheme to search for moth populations. , the current number of iterations is The maximum number of iterations is And the data search space dimension of warehouse product inventory optimization solutions in different situations is ; The warehouse product inventory optimization solution data set under different situations is used as the warehouse product inventory optimization solution data search space under different situations, and randomly generates Each of the warehouse product inventory optimization solution data under different conditions is used as an inventory optimization solution search flame individual, and each inventory optimization solution search moth individual in the inventory optimization solution search moth population is assigned an inventory optimization solution search flame individual; S622, calculating the fitness value of the inventory optimization scheme search flame individual corresponding to each inventory optimization scheme search moth individual, sorting the inventory optimization scheme search flame individuals corresponding to each inventory optimization scheme search moth individual from large to small according to the fitness value, and selecting the inventory optimization scheme search flame individual with the highest fitness value as the current optimal individual; the fitness value calculation formula is as follows: , in, Indicates The fitness value of the inventory optimization scheme searching for moth individuals corresponding to the inventory optimization scheme searching for flame individuals, Indicates The actual inventory quantity of warehouse products after each delivery in the warehouse product inventory optimization plan data of different situations corresponding to each flame individual is searched for by inventory optimization plan. Indicates Search the supply times in the warehouse product inventory optimization plan data for different situations corresponding to each flame individual. Indicates the standard inventory quantity of the warehouse product corresponding to the real-time demand data of the target warehouse product currently being searched for real-time inventory optimization solutions. Indicates the correction value; S623, dynamically update the number of flame individuals searched by the inventory optimization scheme through the number of iterations, and discard the flame individuals searched by the inventory optimization scheme with lower fitness values; the update formula is as follows: , in, Indicates The number of flame individuals searched by the inventory optimization scheme during the iteration, Represents a function that performs a rounding operation according to the rounding principle; S624, each individual in the inventory optimization scheme search moth population will adopt a logarithmic spiral motion strategy in the warehouse product inventory optimization scheme data search space under different conditions to move around the corresponding individual flame to update the position; the position update formula is as follows: , in, Indicates that the inventory optimization scheme searches for the first The inventory optimization scheme searches for the position of the moth individual after the position update, Indicates The distance between a moth individual and its corresponding flame individual, It represents the logarithmic spiral curve parameters that define the movement of the moth individuals to the flame individuals. represents a random number that is uniformly distributed between [-1,1]. Indicates The inventory optimization scheme searches for the location of the flame individuals corresponding to the inventory optimization scheme searching for the moth individuals; S625, calculating the fitness value of each inventory optimization scheme searching moth individual in the inventory optimization scheme searching moth population after the position is updated, if the fitness value of the inventory optimization scheme searching moth individual after the position is updated is greater than the fitness value of the inventory optimization scheme searching flame individual corresponding to the inventory optimization scheme searching moth individual, then updating the position of the inventory optimization scheme searching flame individual corresponding to the inventory optimization scheme searching moth individual to the position after the position is updated; otherwise, retaining the position of the inventory optimization scheme searching flame individual corresponding to the inventory optimization scheme searching moth individual; Re-sort the flame search individuals of the inventory optimization scheme corresponding to the moth search individuals of the inventory optimization scheme from large to small according to the fitness value, and select the flame search individual of the inventory optimization scheme with the highest fitness value as the new current optimal individual; S626, determine the current number of iterations Is it less than the maximum number of iterations? , if the current number of iterations Less than the maximum number of iterations , then the current number of iterations Add 1 and return to S623; otherwise, take the current optimal individual as the global optimal solution, and retain the warehouse product inventory optimization solution data for different situations corresponding to the global optimal solution; S627. Repeat steps S621 to S626 until all the target warehouse product real-time demand data in the target warehouse product real-time demand data set are traversed, and all retained warehouse product inventory optimization plan data for different situations are data-identified to generate a target warehouse product real-time inventory optimization plan data set.

[0029] S7. Build target warehouse product inventory optimization data based on the target warehouse product real-time demand data and the target warehouse product real-time inventory optimization solution data, and push it to the warehouse product inventory optimization platform; S71: The target warehouse product real-time demand data set and the target warehouse product real-time inventory optimization solution dataset Combine data to build product inventory optimization data for target warehouses ; S72: transmitting the target warehouse product inventory optimization data via a wireless communication network Push to the warehouse product inventory optimization platform and execute warehouse product inventory optimization operations.

[0030] Embodiment 2 is as follows: See also Figure 2 , an inventory optimization system based on BPM applied to a warehouse management system, including a warehouse product real inventory quantity data collection module, a warehouse product screening module, a target warehouse product sales volume estimation module, a target warehouse product real-time demand calculation module, a target warehouse product real-time inventory optimization solution search module, and a target warehouse product inventory optimization data construction module; The warehouse product real inventory quantity data collection module collects product return rate data, real-time inventory quantity, inbound quantity of confirmed inbound orders, and outbound quantity of confirmed outbound orders of various warehouse products through the warehouse product inventory optimization platform, and calculates the real inventory quantity data of various warehouse products to generate the real inventory quantity data of warehouse products; The warehouse product screening module performs numerical comparison processing on the real inventory quantity data of the warehouse product and the set safety inventory quantity threshold, and generates the real inventory quantity data of the target warehouse product according to the numerical comparison result; The target warehouse product sales volume estimation module performs target warehouse product sales volume estimation processing based on the collected target warehouse product historical sales volume data and target warehouse product sales volume fluctuation data, and generates target warehouse product real-time sales volume estimation data; The target warehouse product real-time demand quantity calculation module calculates the demand quantity data of various warehouse products in normal state in the next sales cycle according to the real-time sales volume estimation data of the target warehouse product and the actual inventory quantity data of the target warehouse product, and generates the real-time demand quantity data of the target warehouse product; The target warehouse product real-time inventory optimization solution search module performs real-time inventory optimization solution search processing on the target warehouse product real-time demand data and the established warehouse product inventory optimization solution data for different situations through a moth-to-flame optimization algorithm, searches for the warehouse product inventory optimization solution data for different situations that matches the target warehouse product real-time demand data, performs data identification, and generates the target warehouse product real-time inventory optimization solution data; The target warehouse product inventory optimization data construction module constructs the target warehouse product inventory optimization data by combining the target warehouse product real-time demand data set and the target warehouse product real-time inventory optimization solution data set, pushes it to the warehouse product inventory optimization platform through the wireless communication network, and executes the warehouse product inventory optimization operation.

[0031] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", 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 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 can be combined in any one or more embodiments or examples in a suitable manner.

[0032] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the invention, so that those skilled in the art can understand and use the invention well.

Claims

1. A BPM-based inventory optimization method for a warehouse management system, characterized in that: The steps include: S1. Collect the actual inventory quantity data of warehouse products; S2. Setting a safety stock quantity threshold, performing numerical analysis on the real stock quantity data of the warehouse products and the stock quantity threshold, and generating the real stock quantity data of the target warehouse products; S3, collecting historical sales data of target warehouse products and sales change ratio data of target warehouse products; S4, performing sales estimation processing on the target warehouse product according to the historical sales data of the target warehouse product and the sales change ratio data of the target warehouse product, and generating real-time sales estimation data on the target warehouse product; S5. Calculate the real-time demand data of the target warehouse product according to the real-time sales volume estimation data of the target warehouse product and the actual inventory quantity data of the target warehouse product; S6. Establish inventory optimization solution data for warehouse products under different situations, perform real-time inventory optimization solution search processing on the inventory optimization solution data for warehouse products under different situations and the real-time demand data of the target warehouse products, and generate real-time inventory optimization solution data for the target warehouse products; S7. Build target warehouse product inventory optimization data based on the target warehouse product real-time demand data and the target warehouse product real-time inventory optimization solution data, and push it to the warehouse product inventory optimization platform.

2. The inventory optimization method based on BPM applied to a warehouse management system according to claim 1, characterized in that: The S1 comprises the following steps: S11. Collect product return rate data of various warehouse products through the warehouse product inventory optimization platform to generate a warehouse product return rate data set ,in, Indicates Product return rate data for warehouse-like products; S12, collect the real-time inventory quantity of various warehouse products, the inbound quantity of confirmed inbound orders and the outbound quantity of confirmed outbound orders online through the warehouse product inventory optimization platform, and combine the The warehouse product return rate data in the warehouse is used to calculate the actual inventory quantity data of various warehouse products, and generate a warehouse product actual inventory quantity data set ,in, Indicates The actual inventory quantity data of warehouse-like products; the calculation formula is as follows: ， in, , as well as Respectively represent the collected The real-time inventory quantity of warehouse-like products, the inbound quantity of confirmed inbound orders, and the outbound quantity of confirmed outbound orders.

3. The inventory optimization method based on BPM applied to a warehouse management system according to claim 2, characterized in that: The S2 comprises the following steps: S21. Set the first safety stock quantity threshold to And the second safety stock quantity threshold is ; S22, the The actual inventory quantity data of each warehouse product in the and the Perform numerical comparison and generate a data set of the actual inventory quantity of the target warehouse products based on the numerical comparison results ,in, Indicates The actual inventory quantity data corresponding to the warehouse products in normal status; S221, select the The The actual inventory quantity data of the warehouse products is different from the and the Perform numerical comparisons; like , then it means The actual inventory quantity of warehouse-like products is out of stock, and urgent replenishment instructions are issued to the supply side through the warehouse product inventory optimization platform; like , then it means The actual inventory quantity of warehouse-like products is in normal state and no operation is performed; like , then it means The actual inventory quantity of this type of warehouse products is in excess. The warehouse product inventory optimization platform is used to cancel the first All unconfirmed incoming orders for such warehouse products and suspend replenishment operations for such warehouse products; S222, repeat the steps in S221 until the After the real inventory quantity data of all warehouse products in the , the real inventory quantity data corresponding to all warehouse products in normal state are screened out and the data is marked to generate the .

4. The inventory optimization method based on BPM applied to a warehouse management system according to claim 3 is characterized in that: The S3 comprises the following steps: S31, collect the above information online through the warehouse product inventory optimization platform The historical sales data of the warehouse products corresponding to the actual inventory quantity data of each target warehouse product in the previous sales cycle are used to generate the historical sales data set of the target warehouse products ,in, Indicates The historical sales data of the warehouse products in normal condition in the previous sales cycle; S32, collect the above information online through the warehouse product inventory optimization platform The sales volume change ratio data of warehouse products corresponding to the actual inventory quantity data of each target warehouse product in the previous sales cycle is used to generate the sales volume change ratio data set of the target warehouse products. ,in, Indicates The sales volume change ratio data of the warehouse products in normal status in the previous sales cycle.

5. The inventory optimization method based on BPM applied to a warehouse management system according to claim 4, characterized in that: The S4 comprises the following steps: S41. According to the The historical sales data of the target warehouse products and the The sales fluctuation data of the target warehouse products in the target warehouse are used to estimate the sales of the target warehouse products, and a real-time sales estimate data set of the target warehouse products is generated. ,in, Indicates The estimated sales volume of the warehouse products in normal condition in the next sales cycle, and .

6. The inventory optimization method based on BPM applied to a warehouse management system according to claim 5, characterized in that: The S5 comprises the following steps: S51, according to The target warehouse product real-time sales forecast data and the The real inventory quantity data of the target warehouse products in the target warehouse is used to calculate the demand of various warehouse products in normal state in the next sales cycle, and generate the real-time demand data set of the target warehouse products. ,in, Indicates The demand data of the warehouse products in normal state in the next sales cycle, and .

7. The inventory optimization method based on BPM applied to a warehouse management system according to claim 6, characterized in that: The S6 comprises the following steps: S61. Establish a data set of warehouse product inventory optimization solutions for different situations ,in, Indicates warehouse product inventory optimization plan data for different situations, Indicates the total number of warehouse product inventory optimization solution data under different situations; S62, using the moth-to-flame optimization algorithm to The real-time demand data of each target warehouse product in the Perform real-time inventory optimization solution search processing, search for different warehouse product inventory optimization solution data that match the real-time demand data of each target warehouse product in the real-time demand data set of the target warehouse product, perform data identification, and generate the real-time inventory optimization solution data set of the target warehouse product ,in, Indicates Real-time inventory optimization solution data corresponding to warehouse products in normal status.

8. The inventory optimization method based on BPM applied to a warehouse management system according to claim 7, characterized in that: The S62 comprises the following steps: S621. Build an inventory optimization scheme to search for moth populations and set the population size to , the current number of iterations is The maximum number of iterations is And the data search space dimension of warehouse product inventory optimization solutions in different situations is ; The As a data search space for warehouse product inventory optimization solutions under different situations, randomly generate Each warehouse product inventory optimization plan data under different conditions is used as an inventory optimization plan search flame individual, and each inventory optimization plan search moth individual is assigned an inventory optimization plan search flame individual; S622, calculating the fitness value of the inventory optimization scheme search flame individual corresponding to each inventory optimization scheme search moth individual; S623, dynamically updating the number of flame individuals searched by the inventory optimization scheme through the number of iterations, and discarding the flame individuals searched by the inventory optimization scheme with a lower fitness value; S624, each inventory optimization solution search moth individual will adopt a logarithmic spiral motion strategy in the warehouse product inventory optimization solution data search space under the different situations to move around the corresponding inventory optimization solution search flame individual to update the position; S625, calculating the fitness value of each inventory optimization scheme search moth individual after the position is updated, if the fitness value of the inventory optimization scheme search moth individual after the position is updated is greater than the fitness value of its corresponding inventory optimization scheme search flame individual, then the position of its corresponding inventory optimization scheme search flame individual is updated to the position of the inventory optimization scheme search moth individual after the position is updated; otherwise, retain the position of its corresponding inventory optimization scheme search flame individual; Select the inventory optimization solution with the highest fitness value to search for the flame individual as the current optimal individual; S626, Judgment Is it less than ,like Less than ,but Add 1 and return to S623; otherwise, take the current optimal individual as the global optimal solution, and retain the warehouse product inventory optimization solution data for different situations corresponding to the global optimal solution; S627, repeat the steps from S621 to S626 until the After obtaining the real-time demand data of all target warehouse products, all the retained warehouse product inventory optimization plan data under different conditions are marked and generated. .

9. The inventory optimization method based on BPM applied to a warehouse management system according to claim 8, characterized in that: The S7 comprises the following steps: S71, the and stated Combine data to build product inventory optimization data for target warehouses ; S72, transmitting the Push to the warehouse product inventory optimization platform and execute warehouse product inventory optimization operations.

10. A system for implementing the BPM-based inventory optimization method for a warehouse management system as claimed in any one of claims 1 to 9.

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