Sustainable purchasing element adaptation method based on material classification

Abstract

The invention relates to the technical field of material management, and discloses a sustainable purchasing element adaptation method based on material classification. The method comprises the steps of determining a change item of a purchase element; determining purchase material classification based on the change items of the purchase elements; determining a supplier sequence based on the purchase material classification, and determining a material purchase form and a product sales form associated with suppliers in the supplier sequence based on the supplier sequence; determining first vectors corresponding to suppliers in the supplier sequence based on the material purchasing form; determining second vectors corresponding to suppliers in the supplier sequence based on the product sales form; determining the overall transfer cost of each supplier in the supplier sequence; and based on the purchase form and the production form, a purchase graph is constructed, the purchase graph is a directed graph, and nodes included in the purchase graph correspond to supplies provided by suppliers. According to the invention, the problem of dynamically selecting and managing suppliers according to material classification in the purchasing process can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of material management, and in particular to a sustainable procurement factor adaptation method based on material classification. Background Art

[0002] In traditional procurement management, companies usually rely on historical data, experience and suppliers' quotations to make procurement decisions. The procurement process mainly includes demand determination, supplier selection, material procurement, and monitoring and evaluation of supplier performance. First, the company determines the types and quantities of materials required based on its own production needs and operation plans, and then purchases them in turn. Subsequently, companies usually screen suitable suppliers for cooperation based on factors such as suppliers' historical transaction records, quotations, delivery times, and credit ratings. Once the supplier is determined, the company signs a procurement contract with it and monitors the supplier's delivery status and quality throughout the process. Finally, the company conducts a comprehensive evaluation of the supplier based on the timeliness of delivery, the quality of the materials, and the procurement cost, and provides a reference for future procurement decisions.

[0003] However, with the rapid changes in the market environment and the continuous adjustment of corporate needs, traditional procurement methods have gradually exposed their limitations. First, the traditional procurement process lacks the ability to respond quickly to market changes and supplier performance. When procurement factors change, the existing methods cannot adjust the material classification and supplier selection strategy in a timely manner, resulting in delayed procurement decisions and difficulty in adapting to the dynamic market environment. Secondly, traditional methods usually ignore the hidden costs of switching between suppliers. Due to the lack of effective evaluation tools, when faced with multiple suppliers providing similar materials, it is difficult for enterprises to accurately calculate the switching costs between different suppliers, which may lead to additional procurement costs and supply chain risks. In addition, the existing technology lacks intelligent support tools for supplier selection and cannot help enterprises quickly make the best procurement decisions in a complex supplier network. This problem of insufficient decision support makes it easy for enterprises to get into trouble when facing increasingly complex supply chain management challenges, increasing operational risks and costs. Summary of the invention

[0004] In view of this, the present invention provides a sustainable procurement factor adaptation method based on material classification, which solves the problem of how to dynamically select and manage suppliers according to material classification during the procurement process.

[0005] Specifically, the present application is implemented through the following technical solutions: A first aspect of the present invention provides a sustainable procurement factor adaptation method based on material classification, comprising: Determine changes to procurement elements; Determine the classification of purchased materials based on changes in procurement elements; Determine the supplier sequence based on the classification of purchased materials, and determine the material procurement form and product sales form associated with the suppliers in the supplier sequence based on the supplier sequence; Determine the first vector corresponding to the supplier in the supplier sequence based on the material procurement form; Determine a second vector corresponding to a supplier in the supplier sequence based on the product sales form; Determine the overall transfer cost of each supplier within the supplier sequence; A procurement graph is constructed based on the procurement form and the production form, and the procurement graph is a directed graph, and the nodes contained in the procurement graph correspond to the materials provided by the suppliers.

[0006] According to one embodiment of the present invention, the first vector is determined in the following manner: Obtaining a monthly cost calculated on a monthly basis within a first time window, wherein the monthly cost is determined according to a material purchase form associated with materials provided by a supplier, and the monthly cost includes a material cost sequence and a material cost sequence; According to the material cost sequence, the material cost exponential moving average sequence is obtained. Obtain the material cost exponential moving average series based on the material cost series; Obtain the first difference sequence according to the material cost sequence and the material cost exponential moving average sequence; Obtain the second difference sequence according to the material cost sequence and the material cost exponential moving average sequence; Add the first difference sequence and the second difference sequence according to a preset weight value to obtain a first vector; The material cost is obtained according to a first purchase form associated with the materials provided by the supplier, and the material cost is obtained according to a material pricing result associated with the materials provided by the supplier.

[0007] According to one embodiment of the present invention, the second vector is determined in the following manner: Obtain the product identification sequence of production raw materials including materials provided by suppliers, and obtain the associated pricing form according to the product identification sequence; Get product cost value according to the pricing form; Obtain a first difference sequence of product cost values ​​on a monthly basis within the second time window as the second vector.

[0008] According to one embodiment of the present invention, the overall transfer cost of the supplier is determined based on the transfer cost when the materials provided by one supplier are transferred to the materials provided by other suppliers in the supplier sequence; The transfer cost is calculated based on the purchase graph, the first vector and the second vector; Among them, the weight value between two nodes in the procurement graph is the change in unit cost of procurement and production when the materials are switched from one supplier to another supplier.

[0009] According to one embodiment of the present invention, the weight value calculation process between two nodes in the procurement graph includes: Obtain a first cost value sequence of a form item associated with materials provided by a first supplier corresponding to the first node; Acquire a second cost value sequence of a form item associated with materials provided by a second supplier corresponding to the second node; According to the preconfigured first time point and second time point, a first cost value generated by the first supplier providing materials is obtained based on the first cost value sequence; According to the preconfigured third time point and the second time point, obtaining a second cost value generated by the materials provided by the second supplier based on the second cost value sequence; A weight value from the first node to the second node is obtained based on the first cost value and the second cost value.

[0010] According to one embodiment of the present invention, the transfer cost is the product of the weight and the stability coefficient; The stability coefficient is obtained through a stability model, the input of the stability model is a first vector and a second vector, the output of the stability model is the stability coefficient, and the stability model is a back-propagation multi-layer perceptron.

[0011] According to one embodiment of the present invention, a method for calculating the overall transfer cost of a supplier includes: Traverse the supplier sequence and obtain the transfer cost sequence from supplier to supplier in the supplier sequence; Determine the actual purchase value of products or services provided by each supplier in the supplier sequence based on the historical transaction form, and determine the weight of each supplier in the supplier sequence; The overall transfer cost of suppliers is determined based on the weight of each supplier and the transfer cost sequence of suppliers.

[0012] According to one embodiment of the present invention, the supplier sequence is sorted from high to low according to the overall transfer cost, and prompt information is generated based on the sorting result.

[0013] The second aspect of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the sustainable procurement factor adaptation method based on material classification according to the first aspect of the present invention is implemented.

[0014] The third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the sustainable procurement factor adaptation method based on material classification according to the first aspect of the present invention.

[0015] The technical solution of the present invention includes at least the following technical effects: 1. By dynamically adjusting procurement factors and material classification, procurement needs can be matched more accurately, improving the accuracy of supplier selection; 2. By constructing a directed procurement graph and calculating the transfer costs between suppliers, the hidden costs of supplier switching can be effectively reduced and the procurement process can be optimized; 3. By introducing a stability model, the stability of suppliers can be quantitatively evaluated, thereby better controlling risks in supplier selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which: Figure 1 is a flow chart of a sustainable procurement factor adaptation method based on material classification according to an embodiment of the present application; Figure 2 is a flow chart of a first vector calculation method according to an embodiment of the present application; Figure 3 is a flow chart of a second vector calculation method according to an embodiment of the present application; Figure 4 It is a flow chart of the method for calculating the overall transfer cost of suppliers in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The present disclosure will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and thus implement the present disclosure, rather than implying any limitation on the scope of the present disclosure.

[0018] As used herein, the term "including" and its variants are to be interpreted as open-ended terms meaning "including but not limited to". The term "based on" is to be interpreted as "based at least in part on". The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment". The term "another embodiment" is to be interpreted as "at least one other embodiment". The orientation or position relationship indicated by the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inner", "outer", "vertical", "horizontal", "lateral", "longitudinal" and the like is based on the orientation or position relationship shown in the accompanying drawings. These terms are mainly for better describing the present application and its embodiments, and are not used to limit the indicated devices, elements or components to have a specific orientation, or to be constructed and operated in a specific orientation. In addition, in addition to being used to indicate an orientation or position relationship, some of the above terms may also be used to indicate other meanings, such as the term "upper" may also be used to indicate a certain dependency or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in this application can be understood according to the specific circumstances. In addition, the terms "install", "set", "provided with", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be an internal connection between two devices, elements or components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components. Unless otherwise specified, "plurality" means two or more.

[0019] In traditional procurement management, the selection and management of suppliers often rely on experience and historical data. Enterprises usually decide on procurement plans based on historical transaction data, supplier quotations, delivery records and other factors. However, these methods lack in-depth analysis of the materials provided by suppliers, especially when dealing with dynamically changing market demands and complex procurement environments. Therefore, it is urgent to provide a method that can dynamically select and manage suppliers based on material classification to improve the accuracy and reliability of procurement decisions.

[0020] According to one embodiment of the present invention, Figure 1 This is a flow chart of a sustainable procurement factor adaptation method based on material classification of the present invention, such as Figure 1 As shown, the present invention provides a sustainable procurement factor adaptation method based on material classification, comprising: S1. Determine the changes to the procurement elements; In this step, optionally, the method for determining the changes in procurement elements may be one or more of historical data analysis, market research, supplier evaluation, demand change analysis, risk assessment, policy and regulatory changes, and internal feedback. Through the above methods, the enterprise can effectively identify procurement elements that need to be adjusted and ensure that the procurement strategy can adapt to changes in the external environment and shifts in internal demand.

[0021] S2. Determine the classification of purchased materials based on the changes in the procurement elements; Optionally, when determining the classification of purchased materials, first analyze the impact of the change on the demand, supply risk, cost structure, etc. of the materials, and then redefine the classification standards of the materials based on these impacts. Reclassify the materials by purpose, procurement frequency, supply risk, characteristics and other dimensions to ensure that the procurement strategy can effectively respond to new market and demand changes.

[0022] S3. Determine a supplier sequence based on the classification of purchased materials, and determine a material purchase form and a product sales form associated with the suppliers in the supplier sequence based on the supplier sequence; Specifically, the process of determining the supplier sequence based on the classification of purchased materials first requires matching the material classification with potential suppliers, which is usually achieved using a supplier evaluation and selection model.

[0023] Optionally, the supplier evaluation and selection model of the present invention adopts a multi-criteria decision analysis (MCDA) model. MCDA is a method for making decisions under multiple evaluation criteria. In specific applications, important criteria for evaluating suppliers are determined, including cost criteria, quality criteria, delivery time criteria, technical capability criteria, and financial stability criteria. Then, a weight is assigned to each criterion to reflect its importance. Each supplier is scored under each criterion. Specifically, the score can be based on quantitative or qualitative data. After the scoring is completed, the score under each criterion is multiplied by the corresponding weight, and then the weighted scores of all criteria are added to obtain a comprehensive score for each supplier. Suppliers are sorted according to the comprehensive score, and the supplier or supplier sequence with the highest score is selected.

[0024] Next, based on the determined supplier sequence, associated material procurement forms and product sales forms are generated for each supplier. Specifically, the material information provided by the supplier is connected with the enterprise's procurement needs, and a procurement form is generated based on key factors such as actual demand, price, and delivery date. In addition, through the association analysis model, the supplier's supply record is matched with the enterprise's product sales data to generate a product sales form to ensure the consistency of material supply and sales strategy. Through the above steps, the enterprise can accurately match suppliers with material needs and optimize the procurement and sales processes.

[0025] S4. Determine a first vector corresponding to a supplier in the supplier sequence based on the material procurement form; According to one embodiment of the present invention, referring to Figure 2 As shown, the first vector is determined as follows: S401, obtaining a monthly cost calculated on a monthly basis within a first time window, wherein the monthly cost is determined according to a material purchase form associated with materials provided by a supplier, and the monthly cost includes a material cost sequence and a material cost sequence; Among them, the material cost series is obtained based on the cost of raw materials or components provided by suppliers; the material cost series is obtained based on the overall cost of the final purchased materials, including all related costs such as raw materials, processing, and transportation.

[0026] S402, obtaining a material cost exponential moving mean sequence according to the material cost sequence, and obtaining a material cost exponential moving mean sequence according to the material cost sequence; Specifically, when calculating the material cost exponential moving mean series and the material cost exponential moving mean series, the material cost series and the material cost series are smoothed to reduce the impact of short-term fluctuations and highlight long-term trends.

[0027] S403, obtaining a first difference sequence according to the material cost sequence and the material cost exponential moving average sequence; S404, obtaining a second difference sequence according to the material cost sequence and the material cost exponential moving average sequence; Specifically, after obtaining the material cost sequence, the material cost sequence and their corresponding moving average sequence, the system calculates the difference sequence between the corresponding cost sequence and the moving average sequence, and reflects the trend and fluctuation of cost changes through the difference sequence.

[0028] S405, adding the first difference sequence and the second difference sequence according to a preset weight value to obtain a first vector; S406, the material cost is obtained according to the first purchase form associated with the material provided by the supplier, and the material cost is obtained according to the material pricing result associated with the material provided by the supplier. Through this method, the accuracy and relevance of the data can be ensured, so that the generated first vector can truly reflect the cost performance of the supplier.

[0029] S5. Determine the second vector corresponding to the supplier in the supplier sequence based on the product sales form; the second vector is used to evaluate the impact of the materials provided by the supplier on the final product cost.

[0030] According to one embodiment of the present invention, referring to Figure 3 As shown, the second vector is determined as follows: S501, obtaining product identification sequences of production raw materials including materials provided by suppliers, and obtaining associated pricing forms according to the product identification sequences; Specifically, the production materials related to the materials provided by the supplier are identified, and the corresponding product identification sequence is obtained. Among them, the product identification is a unique identifier used in the production process and is associated with a specific supplier substance. Therefore, the pricing form associated with it is obtained through these identifications.

[0031] S502, obtaining the product cost value according to the pricing form; Specifically, the product cost values ​​related to the supplier materials are extracted from the associated pricing form. These cost values ​​reflect the contribution of the materials provided by the supplier to the final product. For example, if the raw materials provided by a supplier are used in the production of multiple products, the cost values ​​of these products will include the cost of the supplier materials.

[0032] S503 obtains a first difference sequence of product cost values ​​on a monthly basis within a second time window as a second vector.

[0033] Specifically, in the second time window, a differential sequence is calculated based on the product cost value as the second vector, and the second vector is used to reflect the change of product cost, especially the dynamic impact of supplier materials on product cost.

[0034] S6. Determine the overall transfer cost of each supplier in the supplier sequence; Among them, see Figure 4 As shown, the calculation method of the supplier's overall transfer consideration includes: S601. Traverse the supplier sequence to obtain the transfer cost sequence of suppliers to suppliers in the supplier sequence; traverse the entire supplier sequence to obtain the transfer cost sequence of each supplier relative to other suppliers. Among them, the transfer cost identifies the cost change that the enterprise needs to bear when switching the procurement demand from one supplier to another. In this process, the additional cost that needs to be paid when the procurement demand is switched from one supplier to another will be calculated. These costs include: procurement price differences, logistics and delivery cost differences, quality adjustment differences, and switching risk costs.

[0035] S602: Determine the actual purchase value of the product or service provided by each supplier in the supplier sequence based on the historical transaction form, and determine the weight of each supplier in the supplier sequence; Specifically, based on the historical transaction form, the actual purchase value of the products or services provided by each supplier in the supplier sequence is determined. The actual purchase value can reflect the importance of each supplier in the supply chain. Combined with the supplier's weight, the overall transfer cost not only considers the cost, but also comprehensively considers the importance of the supplier, providing enterprises with a more scientific basis for purchasing decisions.

[0036] S603. Determine the overall transfer cost of suppliers based on the weights of each supplier and the supplier's transfer cost sequence. Calculate the overall transfer cost of each supplier based on the transfer cost sequence and corresponding weight of each supplier. By identifying suppliers with high transfer costs, enterprises can take preventive measures in advance to reduce potential risks caused by supply chain disruptions or supplier switching.

[0037] According to an embodiment of the present invention, the supplier sequence is sorted from high to low according to the overall transfer cost, and prompt information is generated based on the sorting result. Based on the sorting of transfer costs, enterprises can make more intelligent decisions on supplier selection and procurement strategies, thereby reducing overall procurement costs and improving the flexibility and stability of the supply chain.

[0038] According to one embodiment of the present invention, the overall transfer cost of the supplier is determined based on the transfer cost when the materials provided by one supplier are transferred to the materials provided by other suppliers in the supplier sequence; The transfer cost is calculated based on the procurement graph, the first vector and the second vector; wherein the weight value between two nodes in the procurement graph is the change in unit cost of procurement and production links when switching from one supplier providing materials to another supplier providing materials.

[0039] The procurement graph is a directed graph model used to represent the relationship between suppliers. Each node in the graph represents a supplier, and the edges between nodes represent the cost change when switching from one supplier to another. Specifically, each node corresponds to a supplier, and the information in the node includes key indicators such as the historical cost, delivery time, and quality of the materials provided by the supplier; the edge between two nodes represents the unit cost change faced by the enterprise in the procurement and production links when switching from one supplier to another.

[0040] The weight value is the key in the procurement graph, which reflects the cost difference when switching suppliers. Specifically, the weight value calculation process between two nodes in the procurement graph includes: Get the first cost value sequence of the form items associated with the first supplier providing materials corresponding to the first node; first, get the material purchase form related to the first node (first supplier) and extract the cost value sequence associated with it. This sequence includes material cost, transportation cost, storage cost, etc.

[0041] The second cost value sequence of the form items associated with the materials provided by the second supplier corresponding to the second node is obtained; similarly, in the same way as the acquisition method of the first node, the material procurement form related to the second node (second supplier) is obtained, and its cost value sequence is extracted.

[0042] According to the pre-configured first time point and second time point, the first cost value generated by the materials provided by the first supplier is obtained based on the first cost value sequence; the first time point and the second time point: select two time points, and calculate the cost values ​​corresponding to the first time point and the second time point based on the cost data value sequence of the first supplier. These time points can be set based on historical procurement cycles or specific business events.

[0043] According to the preconfigured third time point and second time point, the second cost value generated by the materials provided by the second supplier is obtained based on the second cost value sequence; similarly, the cost value of the second supplier is calculated based on the cost value sequence of the second supplier.

[0044] A weight value from the first node to the second node is obtained based on the first cost value and the second cost value. The weight value reflects the impact of cost changes when switching suppliers. If the weight value is positive, it means that switching suppliers will increase costs; if the weight value is negative, it means that switching suppliers may save costs.

[0045] The transfer cost is the product of the weight and the stability coefficient; The stability coefficient is obtained through a stability model, the input of the stability model is a first vector and a second vector, the output of the stability model is the stability coefficient, and the stability model is a back-propagation multi-layer perceptron.

[0046] Specifically, the stability coefficient is used to quantify the stability of each supplier in the face of cost fluctuations. It is calculated using a Backpropagation Multi-Layer Perceptron (MLP) model. The specific process is as follows: In the first step, the first vector and the second vector are input; the first vector and the second vector reflect the supplier's performance in terms of material cost and final product cost respectively. These vectors are used as inputs to the MLP model, and the model is trained to learn the performance patterns of suppliers in historical data.

[0047] The second step is that the model outputs a stability coefficient. After being trained with a large amount of historical data, the MLP model outputs a stability coefficient, which indicates the stability of the supplier's cost fluctuations. The higher the stability coefficient, the more stable the supplier has been in history and the lower the switching risk.

[0048] The third step is to calculate the overall switching cost of the supplier. Once the weight value and stability coefficient are obtained, the overall switching cost of the supplier can be calculated. Among them, the overall switching cost of the supplier = the stability coefficient of the supplier × the weight value of the supplier switching.

[0049] The fourth step is to sort suppliers and generate prompt information; sort suppliers according to the calculated overall transfer cost. Enterprises can generate prompt information based on the sorting results, such as giving priority to suppliers with lower costs and higher stability, or prompting potential high-risk suppliers, so as to optimize procurement decisions.

[0050] S7. Construct a procurement graph based on the procurement form and the production form, and the procurement graph is a directed graph, and the nodes included in the procurement graph correspond to the materials provided by the supplier.

[0051] According to one embodiment of the present invention, a computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements a sustainable procurement factor adaptation method based on material classification when executing the computer program.

[0052] According to one embodiment of the present invention, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements a sustainable procurement factor adaptation method based on material classification.

[0053] The beneficial effects of the present invention are: Improve the accuracy of procurement decisions by dynamically selecting and managing suppliers based on material classification, and effectively identify and evaluate supplier performance; Optimize supplier selection and management. Multi-criteria decision analysis models and differential sequence analysis methods help enterprises conduct comprehensive evaluation of suppliers under multiple criteria, making supplier selection and management more scientific and systematic. Reduce supplier switching costs and risks. By calculating the overall transfer costs between suppliers, companies can better assess the costs and risks of supplier switching and reduce potential losses caused by improper supplier switching. Improve the stability and efficiency of the supply chain. By introducing the stability coefficient and procurement graph model, enterprises can better manage the stability of suppliers and ensure a smooth and efficient procurement process in a dynamic market environment; Data-driven decision support provides data-based decision support for the overall solution by analyzing historical data and actual transaction data, allowing companies to combine objective data in supplier management rather than simply experience and intuition.

[0054] Those of ordinary skill in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0055] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0056] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0057] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0058] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0059] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the energy-saving signal sending / receiving method of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0060] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the present application.

[0061] It should be understood that the size of the sequence number of each step in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. For the purpose of example and description, the foregoing description of the implementation of the present disclosure has been given. The foregoing description is not exhaustive and is not intended to limit the present disclosure to the exact form disclosed. Various deformations and modifications may exist according to the above teachings, or various deformations and modifications may be obtained from the practice of the present disclosure. These embodiments are selected and described to illustrate the principles of the present disclosure and its practical application, so that those skilled in the art can use the present disclosure in various embodiments and various modifications suitable for the specific purpose conceived.

Claims

1. A sustainable procurement factor adaptation method based on material classification, characterized in that: include: Determine changes to procurement elements; Determine the classification of purchased materials based on changes in procurement elements; Determine the supplier sequence based on the classification of purchased materials, and determine the material procurement form and product sales form associated with the suppliers in the supplier sequence based on the supplier sequence; Determine the first vector corresponding to the supplier in the supplier sequence based on the material procurement form; Determine a second vector corresponding to a supplier in the supplier sequence based on the product sales form; Determine the overall transfer cost of each supplier within the supplier sequence; A procurement graph is constructed based on the procurement form and the production form, and the procurement graph is a directed graph, and the nodes contained in the procurement graph correspond to the materials provided by the suppliers.

2. The sustainable procurement factor adaptation method based on material classification according to claim 1 is characterized in that: The first vector is determined as follows: Obtaining a monthly cost calculated on a monthly basis within the first time window, wherein the monthly cost is determined according to a material purchase form associated with materials provided by the supplier, and the monthly cost includes a material cost sequence and a material cost sequence; According to the material cost sequence, the material cost exponential moving average sequence is obtained. Obtain the material cost exponential moving mean series based on the material cost series; Obtain the first difference sequence according to the material cost sequence and the material cost exponential moving average sequence; Obtain the second difference sequence according to the material cost sequence and the material cost exponential moving average sequence; Add the first difference sequence and the second difference sequence according to a preset weight value to obtain a first vector; The material cost is obtained according to a first purchase form associated with the materials provided by the supplier, and the material cost is obtained according to a material pricing result associated with the materials provided by the supplier.

3. The sustainable procurement factor adaptation method based on material classification according to claim 1 is characterized in that: The second vector is determined as follows: Obtain the product identification sequence of production raw materials including materials provided by suppliers, and obtain the associated pricing form according to the product identification sequence; Get product cost value according to the pricing form; Obtain a first difference sequence of product cost values ​​on a monthly basis within the second time window as the second vector.

4. The sustainable procurement factor adaptation method based on material classification according to claim 1 is characterized in that: The overall transfer cost of the supplier is determined based on the transfer cost when the materials provided by one supplier are transferred to the materials provided by the remaining suppliers in the supplier sequence; The transfer cost is calculated based on the purchase graph, the first vector and the second vector; Among them, the weight value between two nodes in the procurement graph is the change in unit cost of procurement and production when the materials are switched from one supplier to another supplier.

5. The sustainable procurement factor adaptation method based on material classification according to claim 4 is characterized in that: The weight value calculation process between two nodes in the procurement graph includes: Obtaining a first cost value sequence of a form item associated with materials provided by a first supplier corresponding to a first node; Acquire a second cost value sequence of a form item associated with materials provided by a second supplier corresponding to the second node; According to the preconfigured first time point and second time point, a first cost value generated by the first supplier providing materials is obtained based on the first cost value sequence; According to the preconfigured third time point and the second time point, obtaining a second cost value generated by the materials provided by the second supplier based on the second cost value sequence; A weight value from the first node to the second node is obtained based on the first cost value and the second cost value.

6. The sustainable procurement factor adaptation method based on material classification according to claim 4 is characterized in that: The transfer cost is the product of the weight and the stability coefficient; The stability coefficient is obtained through a stability model, the input of the stability model is a first vector and a second vector, the output of the stability model is the stability coefficient, and the stability model is a back-propagation multi-layer perceptron.

7. The sustainable procurement factor adaptation method based on material classification according to claim 1 is characterized in that: The calculation method of the supplier's overall transfer consideration includes: Traverse the supplier sequence and obtain the transfer cost sequence from supplier to supplier in the supplier sequence; Determine the actual purchase value of products or services provided by each supplier in the supplier sequence based on the historical transaction form, and determine the weight of each supplier in the supplier sequence; The overall transfer cost of suppliers is determined based on the weight of each supplier and the transfer cost sequence of suppliers.

8. The sustainable procurement factor adaptation method based on material classification according to claim 1 is characterized in that: The supplier sequence is sorted from high to low according to the overall transfer cost, and prompt information is generated based on the sorting results.

9. Computer device, characterized in that It includes a memory and a processor, the memory stores a computer program, and the processor implements the sustainable procurement factor adaptation method based on material classification as described in any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the sustainable procurement factor adaptation method based on material classification as described in any one of claims 1 to 8 is implemented.

Images