A multi-objective production component allocation method, device and computer equipment

Abstract

The present application discloses a multi-objective production component allocation method, apparatus and computer equipment, the method comprising: determining at least one best-selling product from a plurality of products; obtaining the inventory quantity of core components; obtaining the product configuration of the best-selling product, the product configuration being able to show the plurality of core components required to produce the best-selling product and the corresponding quantity of the core components; determining a plurality of allocation schemes based on the inventory quantity and the product configuration, the allocation schemes being used to show the quantity of allocating the core components in inventory to each of a plurality of production units; linearly optimizing the plurality of allocation schemes based on at least two allocation objectives, and determining the optimal scheme for allocating the core components from the plurality of allocation schemes; wherein the allocation objective is used to show the differences among the plurality of allocation schemes.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a multi-objective production component allocation method, device and computer equipment. Background Art

[0002] For the manufacturing industry, especially for companies with a large supply chain, fluctuations in the upstream supply chain will lead to reduced production efficiency of downstream manufacturing companies, among which large multinational manufacturing companies are particularly affected. The main reason is that such companies have multiple factories in various regions around the world, and their products are diverse, requiring a large number and variety of core components. Therefore, when the supply of core components cannot meet the needs of various products in various factories, how to complete the distribution of core components more efficiently is an urgent problem to be solved. Summary of the invention

[0003] To solve one or more aspects of the above technical problems, the present application provides a multi-objective production component allocation method, apparatus and computer equipment.

[0004] The technical solution of this application is implemented as follows:

[0005] According to the first aspect of the present application, a multi-objective production component allocation method is provided, which is executed based on a computer device, and the method includes: determining at least one best-selling product from a plurality of products; obtaining the inventory quantity of core components; obtaining the product configuration of the best-selling product, wherein the product configuration can show the plurality of core components required to produce the best-selling product and the corresponding quantity of core components; determining a plurality of allocation schemes based on the inventory quantity and the product configuration, wherein the allocation schemes are used to show the quantity of allocating the core components in stock to each production unit in a plurality of production units; linearly optimizing the plurality of allocation schemes based on at least two allocation targets, and determining the optimal scheme for allocating core components from the plurality of allocation schemes; wherein the allocation target is used to show the differences among the plurality of allocation schemes.

[0006] According to one embodiment of the present application, determining at least one best-selling product from a plurality of products comprises: obtaining sales data of the plurality of products, the sales data comprising backorder data, historical order data and predicted order data of a plurality of production units for the plurality of products; determining a total backorder quantity, a historical total order quantity and a predicted total order quantity for the plurality of products; and performing weighted processing based on the total backorder quantity, the historical total order quantity and the predicted total order quantity to determine at least one best-selling product of the plurality of products.

[0007] According to one embodiment of the present application, a plurality of allocation schemes are determined based on the inventory quantity and the product configuration, including: allocating the core components in stock to the corresponding production units with backorder records shown in the sales data according to the product configuration; determining the remaining core components based on the inventory quantity, the remaining core components being used to show the number of core components remaining after allocating the production units with backorder records; and allocating the remaining core components to multiple production units according to the number of core components required for each set of the best-selling product in the product configuration of the best-selling product.

[0008] According to one embodiment of the present application, the allocation target includes a first difference and a second difference of allocation schemes, the first difference is used to show the allocation differences of multiple core components allocated to production units, and the second difference is used to show the allocation differences of products in the allocation schemes; accordingly, the multiple allocation schemes are linearly optimized based on at least two allocation targets, and the optimal scheme for allocating core components is determined from the multiple allocation schemes, including: determining the first difference and the second difference of the allocation schemes; taking a weighted sum of the first difference and the second difference of the allocation schemes to determine the overall difference of the allocation schemes; and determining the allocation scheme with the smallest overall difference among the multiple allocation schemes as the optimal scheme.

[0009] According to one embodiment of the present application, determining the first difference and the second difference of an allocation scheme includes: determining multiple factory satisfaction rates of the allocation scheme for multiple production units; determining a first maximum and a first minimum of the multiple factory satisfaction rates; determining the difference between the first maximum and the first minimum as the first difference; determining multiple product satisfaction rates of the allocation scheme for multiple best-selling products; determining a second maximum and a second minimum of the multiple product satisfaction rates; and determining the difference between the second maximum and the second minimum as the second difference.

[0010] According to one embodiment of the present application, determining multiple factory fulfillment rates of the allocation scheme for multiple production units includes: obtaining the expected demand for the core components by the multiple production units; and determining the factory fulfillment rate of the allocation scheme for the production units as the ratio of the number of core components allocated to the production units in the allocation scheme to the expected demand of the corresponding production units.

[0011] According to one embodiment of the present application, determining multiple product fulfillment rates of the allocation scheme for multiple best-selling products includes: obtaining expected demand for the multiple best-selling products; and determining the multiple product fulfillment rates of the allocation scheme for the multiple best-selling products as the ratio of the number of complete sets of the multiple best-selling products in the allocation scheme to the expected demand for the corresponding best-selling products.

[0012] According to one embodiment of the present application, the linear optimization of the multiple allocation schemes based on at least two allocation targets and determining the optimal scheme for allocating core components from the multiple allocation schemes include: determining the priority order and setting a threshold range of the allocation targets; according to the priority order, based on the set threshold range of the allocation target of the first priority order, screening out the allocation schemes that meet the set threshold range of the allocation target of the first priority order from the multiple allocation schemes; according to the priority order, based on the set threshold range of the allocation target of the second priority order, screening out the allocation schemes that meet the set threshold range of the allocation target of the second priority order from the allocation schemes that meet the set threshold range of the allocation target of the first priority order; in this way, according to the priority order, the screening of multiple allocation schemes based on all allocation targets is completed to obtain the optimal scheme.

[0013] According to the second aspect of the present application, a multi-objective production component allocation device is also provided, the device comprising: a determination module, used to determine at least one best-selling product from multiple products; an inventory acquisition module, used to acquire the inventory quantity of core components; a configuration acquisition module, used to acquire the product configuration of the best-selling product, the product configuration being able to show the multiple core components required to produce the best-selling product and the corresponding quantity of core components; an allocation module, used to determine multiple allocation schemes based on the inventory quantity and the product configuration, the allocation being used to show an allocation scheme of allocating the core components in stock to multiple production units to produce multiple best-selling products; an optimization module, used to linearly analyze the multiple allocation schemes based on at least two allocation targets, and determine the optimal scheme for allocating core components from the multiple allocation schemes; wherein the allocation target is used to show the fairness of the multiple allocation schemes.

[0014] According to the third aspect of the present application, a computer device is also provided, which includes at least one processor, and at least one memory and a bus connected to the processor; wherein the processor and the memory communicate with each other through the bus; and the processor is used to call program instructions in the memory to execute the above-mentioned multi-objective production component allocation method.

[0015] The multi-objective production component allocation method, device and computer equipment provided by the embodiments of the present application determine at least one best-selling product from multiple products, and obtain the inventory quantity of core components and the product configuration of the best-selling product. The product configuration can show the multiple core components required to produce the best-selling product and the corresponding number of core components. Further, according to the inventory quantity of the core components and the product configuration of the best-selling product, multiple allocation schemes are determined. The allocation scheme is used to show the number of core components in stock allocated to each production unit in multiple production units, and then linear optimization is performed on the multiple allocation schemes based on at least two allocation targets, and the optimal solution for allocating core components is determined from the multiple allocation schemes, wherein the allocation target is used to show the differences of the multiple allocation schemes. Thus, the multi-objective production component allocation based on linear optimization can efficiently complete the core component allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become readily understood. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-limiting manner, wherein:

[0017] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts.

[0018] Figure 1 A schematic diagram of the implementation process of the multi-objective production component allocation method according to an embodiment of the present application is shown;

[0019] Figure 2 The schematic diagram shows the implementation process of "determining the optimal solution for allocating core components from multiple allocation solutions" in the embodiment of the present application. Figure 1 ;

[0020] Figure 3 A schematic diagram of the implementation process of "determining the first difference and the second difference of the allocation scheme" in an embodiment of the present application is shown;

[0021] Figure 4 The schematic diagram shows the implementation process of "determining the optimal solution for allocating core components from multiple allocation solutions" in the embodiment of the present application. Figure 2 ;

[0022] Figure 5 A schematic diagram of an implementation flow of an application example of the multi-objective production component allocation method according to an embodiment of the present application is shown;

[0023] Figure 6 A schematic diagram of the composition structure of a multi-objective production component allocation device according to an embodiment of the present application is shown;

[0024] Figure 7 A schematic diagram of the composition structure of a computer device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] The principles and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present application, and are not intended to limit the scope of the present application in any way. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0026] The technical solution of the present application is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] Figure 1 A schematic diagram of the implementation flow of the multi-objective production component allocation method according to an embodiment of the present application is shown.

[0028] refer to Figure 1 The multi-objective production component allocation method of the embodiment of the present application is executed based on a computer device and includes at least the following operations: operation 101, determining at least one best-selling product from multiple products; operation 102, obtaining the inventory quantity of core components; operation 103, obtaining the product configuration of the best-selling product, the product configuration can show the multiple core components required to produce the best-selling product and the corresponding quantity of the core components; operation 104, determining multiple allocation schemes based on the inventory quantity and the product configuration, the allocation scheme is used to show the quantity of allocating the core components in the inventory to each production unit in multiple production units; operation 105, linearly optimizing multiple allocation schemes based on at least two allocation targets, and determining the optimal solution for allocating core components from multiple allocation schemes; wherein the allocation target is used to show the differences between multiple allocation schemes.

[0029] In operation 101 , at least one best-selling product is determined from a plurality of products.

[0030] In this embodiment of the present application, sales data of multiple products can be obtained, and the sales data includes backorder data, historical order data, and predicted order data of multiple production units for multiple products. Based on the obtained sales data, the total backorder quantity, historical total order quantity, and predicted total order quantity of the multiple products can be determined. Further, based on the total backorder quantity, historical total order quantity, and predicted total order quantity, weighted processing is performed to determine at least one best-selling product of the multiple products.

[0031] For example, the sales data may be the data shown in Table 1 below.

[0032] Table 1

[0033]

[0034]

[0035] Based on the sales data in Table 1 above, it can be determined that:

[0036] The total backlog of product A is A1 = A11 + A21 + A31;

[0037] The total historical order volume of product A is A2 = A12 + A22 + A32;

[0038] The predicted total order volume of product A is A3=A13+A23+A33.

[0039] Correspondingly, the total backlog quantity B1, the total historical order quantity B2 and the predicted total order quantity B3 of product B can be determined...the total backlog quantity E1, the total historical order quantity E2 and the predicted total order quantity E3 of product E can be determined.

[0040] Since backorders need to be produced first, the weight of backorder data can be set higher here. For example, the weight of backorder data can be set to 50%, or even higher. However, only using historical order data within a set time cannot accurately reflect the product demand trend. The predicted order volume can be obtained by analyzing historical order data over a longer period of time to obtain the product demand trend, and the predicted order volume can be determined based on the product demand trend. Therefore, the weight of the predicted order volume can be set to 30% and the weight of the historical order volume can be set to 20%. In this way, the demand for multiple products is:

[0041] The demand for product A is AX = A1*50%+A2*20%+A3*30%;

[0042] The demand for product B is BX = B1*50%+B2*20%+B3*30%;

[0043] The demand for product C is CX = C1*50% + C2*20% + C*30%;

[0044] The demand for product D is DX = A1*50%+D2*20%+D3*30%;

[0045] The demand for product E EX=A1*50%+E2*20%+E3*30%.

[0046] According to the values ​​of AX, BX, CX, DX and EX, the number of best-selling products is determined. For example, products whose demand value is greater than the set demand threshold can be determined as best-selling products, or products whose demand value is ranked before the set order in the ranking of all products can be determined as best-selling products.

[0047] In operation 102, the inventory quantity of the core component is obtained.

[0048] Here, the inventory quantity of core components can be directly obtained. There can be multiple / multiple core components. It should be noted that the inventory quantity of core components can include all core components that can be put into production immediately, such as the core components that have been shipped by the supplier and are guaranteed to arrive within the set time and the current inventory of each production unit.

[0049] For example: multiple core components include P1, P2, P3, P4 and P5, and the inventory quantities of the core components are C1, C2, C3, C4 and C5 respectively.

[0050] In operation 103 , a product configuration of a best-selling product is obtained. The product configuration can show a plurality of core components required to produce the best-selling product and the quantities of the corresponding core components.

[0051] For example, the best-selling products are determined to be A, B and C. The product configuration of the best-selling products can be shown in Table 2 below:

[0052] Table 2

[0053]

[0054] In operation 104 , a plurality of allocation schemes are determined according to the inventory quantity and the product configuration, where the allocation schemes are used to indicate the quantity of allocating the core components of the inventory to each of the plurality of production units.

[0055] In this embodiment of the present application, the core components in stock can be allocated to the corresponding production units with outstanding order records in the sales data according to the product configuration. Then, the remaining core components are determined according to the inventory quantity, and the remaining core components are used to show the number of core components remaining after the production units with outstanding order records are allocated. Finally, the remaining core components are allocated to multiple production units according to the number of core components required for each set of best-selling products in the product configuration of the best-selling products.

[0056] For example, the core components P1, P2, P3, P4 and P5 with inventory quantities of C1, C2, C3, C4 and C5 need to be allocated to production units: Factory 1, Factory 2 and Factory 3, for the production of best-selling products A, B and C. The backorder quantities of Factory 1, Factory 2 and Factory 3 for products A, B and C are A11, A21 and A31 respectively, the backorder quantities of Factory 1, Factory 2 and Factory 3 for product B are B11, B21 and B31 respectively, and the backorder quantities of Factory 1, Factory 2 and Factory 3 for product C are C11, C21 and C31 respectively. Here, Factory 1, Factory 2 and Factory 3 can be configured to produce core components that can handle backorders based on the product configuration of products A, B and C.

[0057] Then, according to the number of core components required for each set of best-selling products in the product configuration of the best-selling products, the remaining core components after allocating the production units with backorder records are allocated to multiple production units. In this allocation process, the expected production volume of each production unit for multiple production products can be obtained first. For example, the expected production volume of factory 2 for product A can be determined based on the backorder volume A21, historical order volume A22 and predicted order volume A23 of factory 2 for product A. Similarly, the expected production volume of factory 1 for product A, B or C, the expected production volume of factory 2 for product B or C, and the expected production volume of factory 3 for product A, B or C can be determined. In this round of allocation process, according to the expected production volume of each production unit for the product and the corresponding product configuration, factory 1, factory 2 and factory 3 can be allocated in turn, and the number of core components required for a set of products can be allocated. It is also possible to give priority to allocating core components to production units with higher expected production volumes.

[0058] Thus, according to the current inventory quantity of core components, multiple allocation schemes are determined to ensure that the existing inventory of core components can be quickly used to produce best-selling products without the need to purchase additional core components. The multiple allocation schemes can all show the quantity of the inventory of core components allocated to each of the multiple production units. As shown in Table 3 below:

[0059] Table 3

[0060]

[0061]

[0062] Table 3 does not show specific numbers, but is only used to simply show the data content that may be included in the allocation scheme. In actual application, the data may be stored and calculated in a suitable data storage form, such as a database.

[0063] In operation 105, linear optimization is performed on multiple allocation schemes based on at least two allocation targets, and an optimal scheme for allocating core components is determined from the multiple allocation schemes; wherein the allocation target is used to show the differences among the multiple allocation schemes.

[0064] In this embodiment of the present application, the allocation target includes a first difference and a second difference in the allocation plan, the first difference is used to show the allocation difference of multiple core components to production units, and the second difference is used to show the product allocation difference in the allocation plan.

[0065] Specifically, the goals of the core component allocation problem mainly include the following two types of goals: one is to increase the number of product sets, and the other is to ensure the fairness of allocation. Each product is composed of multiple core components, so the product component configuration relationship must be considered during allocation, and because there are multiple factories and multiple products, the differences in satisfaction rates between factories and the differences in satisfaction rates between products must be considered during allocation. Different factories and products have their own needs for different components. Here, the satisfaction rate refers to the ratio of the allocated amount to the expected demand. Here, the first difference can be the difference in satisfaction rates between multiple products, so the first allocation goal is that the first difference is as small as possible. The second difference can be the difference in satisfaction rates between factories, so the second allocation goal is that the second difference is as small as possible.

[0066] In this embodiment of the present application, the implementation process of determining the optimal solution for allocating core components from multiple allocation solutions can refer to the following: Figure 2 The schematic diagram of the implementation process of "determining the optimal solution for allocating core components from multiple allocation solutions" is shown.

[0067] refer to Figure 2 In this embodiment of the present application, linear optimization is performed on multiple allocation schemes based on at least two allocation targets, and the optimal scheme for allocating core components is determined from multiple allocation schemes, which at least includes the following operation flow:

[0068] Operation 201 : determining a first difference and a second difference of allocation schemes.

[0069] In this embodiment of the present application, the first difference and the second difference of the allocation scheme may be determined based on the satisfaction rates of the allocation scheme for the plurality of production units.

[0070] In this embodiment of the present application, determining multiple factory fulfillment rates of an allocation scheme for multiple production units includes: obtaining the expected demand for core components by the multiple production units; and determining the factory fulfillment rate of the allocation scheme for the production units as the ratio of the number of core components allocated to the production units in the allocation scheme to the expected demand of the corresponding production units.

[0071] In this embodiment of the present application, determining multiple product fulfillment rates of an allocation scheme for multiple best-selling products includes: obtaining expected demand for multiple best-selling products; and determining the multiple product fulfillment rates of the allocation scheme for multiple best-selling products as the ratio of the number of complete sets of multiple best-selling products in the allocation scheme to the expected demand for corresponding best-selling products.

[0072] In this embodiment of the present application, the first difference and the second difference can be determined by solving a common satisfaction rate difference method such as the variance or standard deviation of multiple satisfaction rates.

[0073] For example, take the first difference between multiple factories as an example. Assume there are n factories, and the satisfaction rate of the i-th factory is where x i is the component allocation for the ith factory, d i is the expected demand for the core component, the first difference between multiple factories can be expressed as: in That is, the average satisfaction rate.

[0074] However, solving the variance or standard deviation still requires some computing resources and the solving speed is slow. Therefore, in this embodiment of the present application, the following method can be used: Figure 3 The operational flow shown determines a first difference and a second difference in the allocation scheme.

[0075] refer to Figure 3 In this embodiment of the present application, determining the first difference and the second difference of the allocation scheme includes at least the following operation flow: Operation 301, determining the multiple factory satisfaction rates of the allocation scheme for multiple production units. Operation 302, determining the first maximum and the first minimum of the multiple factory satisfaction rates. Operation 303, determining the difference between the first maximum and the first minimum as the first difference. Operation 304, determining the multiple product satisfaction rates of the allocation scheme for multiple best-selling products. Operation 305, determining the second maximum and the second minimum of the multiple product satisfaction rates. Operation 306, determining the difference between the second maximum and the second minimum as the second difference.

[0076] In operation 202 , weighted summation is performed on the first difference and the second difference of the allocation scheme to determine the overall difference of the allocation scheme.

[0077] In this embodiment of the present application, the allocation target may include a first difference for showing the factory allocation difference and a second difference for showing the product allocation difference, so the total difference of the allocation scheme can be obtained by weighted summing the first difference and the second difference. It should be noted that the first difference and the second difference can be directly summed here, and the direct summing of the two is a special form of weighted summing, indicating that the importance weights of the first difference and the second difference to the total difference are both 50%.

[0078] Operation 203, determine the allocation scheme with the smallest overall difference among the multiple allocation schemes as the optimal scheme. Again, take the first difference between different factories as an example. The first difference between multiple factories can be expressed as f max -f min , where f max =max(f i ,i=1,2,3,…),f min =min(f i, i=1,2,3,…). When all satisfaction rates are the same, the standard deviation and range are both 0, reaching the optimum. The allocation target includes the diversity of factory allocation and the diversity of product allocation, so the diversity can be expressed as the sum of factory diversity and product diversity.

[0079] Maximizing fairness is equivalent to minimizing the extreme difference in satisfaction rate, that is, in Indicates the extreme difference in factory satisfaction rate, Indicates the extreme difference in product satisfaction rate.

[0080] Obviously max =max(f i ,i=1,2,3,…),f min =min(f i , i=1,2,3,…) is a logical expression, which is difficult to solve directly. Here, we can perform an equivalent transformation on the problem. The details are as follows:

[0081] Will Equivalently converted into a linear optimization problem:

[0082]

[0083]

[0084]

[0085]

[0086]

[0087] Obviously, the allocation scheme of core components can be optimized through the above linear optimization problem to obtain the optimal allocation scheme for core components. Therefore, by linearly summing multiple difference values ​​and judging the size to perform multi-objective optimization, the complexity of data processing is effectively reduced, the amount of calculation is reduced, the calculation speed and efficiency are improved, and the calculation and storage resources are significantly saved.

[0088] Therefore, this solution targets multiple product types and multiple configuration solutions for each product type, and through linear optimization of the allocation problem in the product production process, significantly reduces the amount of calculation, improves the calculation efficiency, and effectively saves computing resources. It is effectively applicable to the product production component allocation process of large enterprises.

[0089] In another embodiment of the present application, the following can be used: Figure 4 The operation flow shown implements "determining the best solution for allocating core components from multiple allocation solutions".

[0090] refer to Figure 4 In this embodiment of the present application, linear optimization is performed on multiple allocation schemes based on at least two allocation targets, and the optimal scheme for allocating core components is determined from multiple allocation schemes, which at least includes the following operation flow:

[0091] Operation 401 : determining the priority of the allocation targets and setting the threshold range.

[0092] For example, three allocation targets can be set here:

[0093] Objective 1: The total number of complete sets of best-selling products produced by multiple production units, that is, after allocating core components using a specified allocation plan, multiple production units use the allocated core components for production, and the total number of complete sets of multiple best-selling products that can eventually be produced is greater than a first set value.

[0094] Objective 2: A first difference for indicating the variability of allocation of the plurality of core components to the production units is smaller than a second set value.

[0095] Objective 3: The second difference for indicating the variability of product distribution in the distribution plan is less than the third set value.

[0096] The priority order of these three allocation targets, as well as the first set value, the second set value and the third set value can be set according to actual needs. Among them, for the allocation target that the total number of complete sets is greater than the first set value, it can also be set as the allocation scheme with the largest total number of complete sets from all allocation schemes, and the allocation scheme with the largest total number of complete sets can have one or more schemes. For example: Here, the priority order is set as: Target 1 is the first priority order, Target 2 is the second priority order, and Target 3 is the third priority order. And Target 1 is set as the allocation scheme with the largest total number of complete sets from all allocation schemes.

[0097] Operation 402 : According to the priority order and the set threshold range of the allocation target of the first priority order, select an allocation scheme that meets the set threshold range of the allocation target of the first priority order from multiple allocation schemes.

[0098] For example, referring back to the example of operation 401, firstly, the allocation scheme with the largest total number of complete sets among the multiple allocation schemes is screened out. Here, it is assumed that the total number of complete sets of 20 schemes is consistent, and the total number of complete sets of these 20 schemes is greater than the total number of complete sets of other allocation schemes among the multiple allocation schemes.

[0099] Operation 403, according to the priority order, according to the set threshold range of the allocation target of the second priority order, select the allocation scheme that meets the set threshold range of the allocation target of the first priority order from the allocation schemes that meet the set threshold range of the allocation target of the first priority order; in this way, according to the priority order, the screening of multiple allocation schemes according to all allocation targets is completed to obtain the optimal scheme.

[0100] For example, again in combination with the examples in operations 401 and 402, the second priority allocation target can be set to a factory satisfaction rate difference of less than 10%. Here, the allocation scheme with a factory satisfaction rate difference of less than 10% can be screened out from the 20 allocation schemes with the largest total set quantity and the same total set quantity.

[0101] Further, the allocation target of the third priority can be set as the allocation scheme with the smallest difference in product satisfaction rate among the allocation schemes that meet the allocation targets of the first priority and the second priority. Here, the allocation scheme with the smallest difference in product satisfaction rate can be further screened out from the allocation schemes with a difference in factory satisfaction rate of less than 10%.

[0102] The above multi-objective production component allocation targets are allocated using linear calculations and a simple data size comparison process, which significantly reduces the amount of calculations, improves calculation efficiency, and effectively saves computing resources.

[0103] Figure 5 A flowchart of an implementation example of the multi-objective production component allocation method according to an embodiment of the present application is shown.

[0104] refer to Figure 5 The application example of the multi-objective production component allocation method in the embodiment of the present application is to divide the scheme into two modules for execution based on a computer device, and at least include the following operations:

[0105] Operation 501: acquiring original data.

[0106] Includes: data on product types and configuration plans on sale, product backlog data, historical order data and product future demand forecast data, as well as core component inventory data.

[0107] Operation 502, sorting all products according to their popularity, and filtering out the best-selling product types.

[0108] Operation 503 , sorting the configuration solutions of the best-selling products according to the core component inventory data, and screening out the configuration solutions that can be produced quickly.

[0109] In operation 504 , a multi-objective linear optimization is performed on the multiple configuration solutions.

[0110] Operation 505 : solving the problem after the multi-objective linear optimization.

[0111] Among them, operations 501 to 503 are processed by module 1 to screen product configuration solutions. Operations 504 and 505 are processed by module 2 to solve the linear optimization of the configuration solution. The specific implementation process of operations 501 to 505 is the same as Figure 1 The specific implementation process of operations 501 to 505 in the illustrated embodiment is similar and will not be described in detail here.

[0112] The multi-objective production component allocation method provided in the embodiment of the present application determines at least one best-selling product from multiple products, and obtains the inventory quantity of the core component and the product configuration of the best-selling product. The product configuration can show the multiple core components required to produce the best-selling product and the corresponding number of core components. Further, according to the inventory quantity of the core component and the product configuration of the best-selling product, multiple allocation schemes are determined. The allocation scheme is used to show the number of the core components in stock allocated to each production unit in multiple production units, and then linear optimization is performed on the multiple allocation schemes based on at least two allocation targets, and the optimal scheme for allocating the core components is determined from the multiple allocation schemes, wherein the allocation target is used to show the differences of the multiple allocation schemes. Thus, by linearly summing the values ​​of multiple differences and judging the size to perform multi-objective optimization, the complexity of data processing is effectively reduced, the amount of calculation is reduced, the calculation speed and efficiency are improved, and the calculation and storage resources are significantly saved.

[0113] Similarly, based on the above multi-objective production component allocation method, an embodiment of the present application also provides a computer-readable storage medium, which stores a program. When the program is executed by a processor, the processor performs at least the following operation steps: operation 101, determining at least one best-selling product from multiple products; operation 102, obtaining the inventory quantity of core components; operation 103, obtaining the product configuration of the best-selling product, the product configuration can show the multiple core components required to produce the best-selling product and the corresponding quantity of core components; operation 104, determining multiple allocation schemes based on the inventory quantity and product configuration, the allocation scheme is used to show the quantity of allocating the core components in the inventory to each production unit in multiple production units; operation 105, linearly optimizing multiple allocation schemes based on at least two allocation targets, and determining the optimal scheme for allocating core components from multiple allocation schemes; wherein the allocation target is used to show the differences between multiple allocation schemes.

[0114] Further, based on the above multi-objective production component allocation method, the present application embodiment also provides a multi-objective production component allocation device, such as Figure 6The multi-objective production component allocation device 60 includes: a determination module 601, used to determine at least one best-selling product from multiple products; an inventory acquisition module 602, used to acquire the inventory quantity of core components; a configuration acquisition module 603, used to acquire the product configuration of the best-selling product, and the product configuration can show the multiple core components required to produce the best-selling product and the corresponding number of core components; an allocation module 604, used to determine multiple allocation schemes according to the inventory quantity and product configuration, and the allocation is used to show the allocation scheme of allocating the core components in stock to multiple production units to produce multiple best-selling products; an optimization module 605, used to linearize multiple allocation schemes based on at least two allocation targets, and determine the optimal scheme for allocating core components from multiple allocation schemes; wherein the allocation target is used to show the fairness of multiple allocation schemes.

[0115] According to one embodiment of the present application, the determination module 601 includes: a data acquisition sub-module, used to acquire sales data of multiple products, the sales data including backorder data, historical order data and predicted order data of multiple production units for multiple products; an order determination sub-module, used to determine the total backorder quantity, historical total order quantity and predicted total order quantity of multiple products; a best-selling determination sub-module, used to perform weighted processing based on the total backorder quantity, historical total order quantity and predicted total order quantity to determine at least one best-selling product among multiple products.

[0116] According to one embodiment of the present application, the allocation module 604 includes: a first allocation sub-module, which is used to allocate the core components in stock to the corresponding production units with backorder records shown in the sales data according to the product configuration; a second allocation sub-module, which is used to determine the remaining core components based on the inventory quantity, and the remaining core components are used to show the number of core components remaining after the production units with backorder records are allocated; a third allocation sub-module, which is used to allocate the remaining core components to multiple production units according to the number of core components required for each set of best-selling products in the product configuration of the best-selling products.

[0117] According to one embodiment of the present application, the allocation target includes a first difference and a second difference of the allocation scheme, the first difference is used to illustrate the allocation difference of multiple core components to production units, and the second difference is used to illustrate the product allocation difference in the allocation scheme; accordingly, the optimization module 605 includes: a first determination submodule, used to determine the first difference and the second difference of the allocation scheme; a second determination submodule, used to perform weighted summation of the first difference and the second difference of the allocation scheme to determine the overall difference of the allocation scheme; a first scheme determination submodule, used to determine the allocation scheme with the smallest overall difference among multiple allocation schemes as the optimal scheme.

[0118] According to one embodiment of the present application, a first determination submodule determines a first difference and a second difference of an allocation scheme, including: determining a plurality of factory satisfaction rates of the allocation scheme for a plurality of production units; determining a first maximum and a first minimum of the plurality of factory satisfaction rates; determining the difference between the first maximum and the first minimum as the first difference; determining a plurality of product satisfaction rates of the allocation scheme for a plurality of best-selling products; determining a second maximum and a second minimum of the plurality of product satisfaction rates; and determining the difference between the second maximum and the second minimum as the second difference.

[0119] According to one embodiment of the present application, the first determination submodule determines multiple factory fulfillment rates of the allocation plan for multiple production units, including: obtaining the expected demand for core components by multiple production units; and determining the factory fulfillment rate of the allocation plan for the production units as the ratio of the number of core components allocated to the production units in the allocation plan to the expected demand of the corresponding production units.

[0120] According to one embodiment of the present application, the first determination submodule determines multiple product satisfaction rates of the allocation plan for multiple best-selling products, including: obtaining expected demand quantities for multiple best-selling products; and determining the multiple product satisfaction rates of the allocation plan for multiple best-selling products as the ratio of the number of complete sets of multiple best-selling products in the allocation plan to the expected demand quantities of the corresponding best-selling products.

[0121] According to one embodiment of the present application, the optimization module 605 includes: a target determination submodule, which is used to determine the priority and set threshold range of the allocation target; a first screening submodule, which is used to screen out the allocation schemes that meet the set threshold range of the allocation target of the first priority from multiple allocation schemes according to the priority and the set threshold range of the allocation target of the first priority; a second screening submodule, which is used to screen out the allocation schemes that meet the set threshold range of the allocation target of the second priority from the allocation schemes that meet the set threshold range of the allocation target of the first priority according to the priority and the set threshold range of the allocation target of the second priority; in this way, it includes multiple screening submodules, which are used to complete the screening of multiple allocation schemes according to all allocation targets according to the priority and obtain the optimal scheme.

[0122] Furthermore, based on the above multi-objective production component allocation method, the present application embodiment also provides a computer device, such as Figure 7 The computer device 70 includes: at least one processor 701, and at least one memory 702 and a bus 703 connected to the processor 701; wherein the processor 701 and the memory 702 communicate with each other through the bus 703; the processor 701 is used to call the program instructions in the memory 702 to execute the above-mentioned multi-objective production component allocation method.

[0123] It should be noted that the above description of the multi-target production component allocation device and computer equipment embodiment is similar to the above Figures 1 to 5 The description of the method embodiment shown is similar, with the same Figures 1 to 5 The method embodiment shown has similar beneficial effects, so it will not be repeated here. For technical details not disclosed in the embodiments of the multi-target production component allocation device and computer equipment of this application, please refer to the aforementioned Figures 1 to 5 The description of the method embodiment shown in the figure can be understood, and in order to save space, it will not be repeated.

[0124] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0125] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0126] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0127] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0128] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, etc., various media that can store program codes.

[0129] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can essentially or in other words, the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0130] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A multi-objective production component allocation method, executed based on a computer device, the method comprising: Identify at least one best-selling product from among the multiple products; Get the inventory quantity of core components; Acquire a product configuration of the best-selling product, where the product configuration can show a plurality of core components required to produce the best-selling product and the quantity of the corresponding core components; Determine a plurality of allocation schemes according to the inventory quantity and the product configuration, wherein the allocation schemes are used to indicate the quantity of allocating the core components in the inventory to each of the plurality of production units; The production unit is capable of producing the best-selling product according to the quantity of the core components allocated by the allocation plan; Performing linear optimization on the multiple allocation schemes based on at least two allocation objectives, and determining an optimal scheme for allocating core components from the multiple allocation schemes; The allocation target is used to illustrate the differences among the multiple allocation schemes.

2. The method according to claim 1, wherein determining at least one best-selling product from a plurality of products comprises: Acquire sales data of the multiple products, the sales data including backorder data, historical order data, and forecast order data of the multiple products by multiple production units; Determine the total backorder quantity, historical total order quantity and predicted total order quantity of the multiple products; A weighted processing is performed according to the total backlog quantity, the historical total order quantity and the predicted total order quantity to determine at least one best-selling product of the multiple products.

3. The method according to claim 1, wherein the determining multiple allocation schemes according to the inventory quantity and the product configuration comprises: According to the product configuration, the core components in stock are allocated to the corresponding production units with backorder records shown in the sales data; Determine the remaining core components according to the inventory quantity, wherein the remaining core components are used to show the number of core components remaining after the production units with the backorder records are allocated; The remaining core components are allocated to a plurality of production units according to the quantity of core components required for each set of the best-selling product in the product configuration of the best-selling product.

4. The method according to claim 1, wherein the allocation target comprises a first difference and a second difference of the allocation scheme, wherein the first difference is used to show the allocation difference of allocating a plurality of core components to production units, and the second difference is used to show the product allocation difference in the allocation scheme; accordingly, The multiple allocation schemes are linearly optimized based on at least two allocation targets, and an optimal scheme for allocating core components is determined from the multiple allocation schemes, including: determining the first difference and the second difference of the allocation scheme; Performing a weighted summation on the first difference and the second difference of the allocation scheme to determine an overall difference of the allocation scheme; The allocation scheme with the smallest overall difference among the multiple allocation schemes is determined as the optimal scheme.

5. The method of claim 4, determining the first difference and the second difference of the allocation schemes, comprising: determining a plurality of plant fulfillment rates of the allocation plan for a plurality of production units; determining first maximum values ​​and first minimum values ​​of the satisfaction rates of the plurality of factories; Determine a difference between the first maximum value and the first minimum value as the first difference; determining a plurality of product fulfillment rates of the allocation plan for a plurality of best-selling products; Determine second maximum values ​​and second minimum values ​​of the satisfaction rates of the plurality of products; The difference between the second maximum value and the second minimum value is determined as the second difference.

6. The method according to claim 5, determining a plurality of factory fulfillment rates of the allocation scheme for a plurality of production units, comprising: Obtaining expected demand quantities of the core components by the multiple production units; The ratio of the number of core components allocated to the production unit in the allocation plan to the expected demand of the corresponding production unit is determined as the factory satisfaction rate of the allocation plan for the production unit.

7. The method according to claim 5, determining a plurality of product fulfillment rates of the allocation scheme for a plurality of best-selling products, comprising: Obtaining expected demand for the plurality of best-selling products; The ratio of the complete set quantity of multiple best-selling products in the allocation plan to the expected demand quantity of the corresponding best-selling products is determined as the multiple product satisfaction rates of the allocation plan for the multiple best-selling products.

8. The method according to claim 1, wherein the linear optimization of the multiple allocation schemes based on at least two allocation targets and determining the optimal scheme for allocating core components from the multiple allocation schemes comprises: Determining priorities and setting threshold ranges for the allocation targets; According to the priority order, based on the set threshold range of the allocation target of the first priority order, an allocation scheme that meets the set threshold range of the allocation target of the first priority order is screened out from multiple allocation schemes; According to the priority order, based on the set threshold range of the allocation target of the second priority order, the allocation scheme that meets the set threshold range of the allocation target of the first priority order is screened out from the allocation schemes that meet the set threshold range of the allocation target of the first priority order; In this way, according to the priority order, multiple allocation schemes are screened according to all allocation targets to obtain the optimal scheme.

9. A multi-objective production component allocation device, the device comprising: A determination module, used for determining at least one best-selling product from a plurality of products; Inventory acquisition module, used to obtain the inventory quantity of core components; A configuration acquisition module, used to acquire the product configuration of the best-selling product, wherein the product configuration can show a plurality of core components required to produce the best-selling product and the quantity of the corresponding core components; an allocation module, configured to determine a plurality of allocation schemes according to the inventory quantity and the product configuration, wherein the allocation schemes are used to indicate the quantity of allocating the core components of the inventory to each of the plurality of production units; The production unit is capable of producing the best-selling product according to the quantity of the core components allocated by the allocation plan; An optimization module, configured to linearly analyze the plurality of allocation schemes based on at least two allocation targets, and determine an optimal scheme for allocating core components from the plurality of allocation schemes; The allocation target is used to illustrate the differences among the multiple allocation schemes.

10. A computer device, comprising at least one processor, and at least one memory and a bus connected to the processor; wherein: The processor and the memory communicate with each other via the bus; The processor is used to call the program instructions in the memory to execute the multi-objective production component allocation method according to any one of claims 1-8.

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