Interactive intelligent decision-making method and device for supply chain and medium

Abstract

The invention relates to the technical field of resource management, in particular to an interactive intelligent decision-making method and device for a supply chain and a medium, and the method achieves the integration of multi-dimensional information through the comprehensive analysis of the supply amount of a plurality of supply sides and the demand amount of a plurality of demand sides, provides a complete data basis for decision-making, and improves the decision-making efficiency. The initial priority is determined by integrating the demand quantity vector and the historical demand quantity vector, and the historical data is introduced as a quantitative basis, so that subjective deviation caused by purely depending on experience is avoided, the priority division of the product category better conforms to an actual supply and demand rule, a user is allowed to perform interactive intervention, a decision result better adapts to an actual scene, and the user experience is improved. The target mapping function is dynamically determined for different product categories, and the reference weight is calculated in combination with the transmission distance between the supply side and the demand side, so that resource allocation not only considers the supply-demand relationship, but also considers actual constraints such as transportation cost, thereby improving the accuracy and flexibility of supply chain decision making.

Description

Technical Field

[0001] The present invention relates to the technical field of resource management, and in particular to an interactive intelligent decision-making method, device and medium for a supply chain. Background Art

[0002] In modern supply chain management, the supply chain network usually contains multiple supply-side nodes and multiple demand-side nodes, and the product categories involved are increasing day by day. The supply and demand relationship is becoming more dynamic and complex.

[0003] Traditional supply chain decision-making methods often find it difficult to efficiently integrate multi-dimensional information such as supply from multiple supply sides and demand from multiple demand sides. Especially in scenarios with a wide range of product categories, information fragmentation is prone to occur, resulting in incomplete decision-making basis. Traditional methods often rely on manual experience and judgment, and lack quantitative analysis based on historical data and actual demand, which may lead to insufficient supply of high-priority products or excessive allocation of low-priority products.

[0004] Furthermore, traditional approaches lack dynamic adaptability. Parameters in the supply chain, such as demand and transmission distances, can fluctuate over time and with market changes. Traditional static decision-making models are unable to respond to these changes in real time, making it difficult to flexibly adjust allocation strategies. Furthermore, traditional approaches have low user engagement. The decision-making process is often a one-way algorithmic output, lacking interactive user intervention. This makes it impossible to incorporate managers' experience and knowledge to adjust key parameters such as priorities, resulting in a disconnect between decision-making results and actual business scenarios.

[0005] These issues can lead to irrational allocation of supply chain resources, excessively high transportation costs, and inefficient supply-demand matching, impacting the overall competitiveness of the supply chain. Therefore, improving the accuracy and flexibility of supply chain decision-making has become an urgent issue to be addressed. Summary of the Invention

[0006] In response to the above technical problems, the technical solution adopted by the present invention is an interactive intelligent decision-making method for a supply chain, which includes the following steps: S101, at a preset time point, obtaining supply quantity vectors corresponding to M supply sides and basic demand quantity vectors corresponding to N demand sides, wherein the supply quantity vectors include supply quantities corresponding to K product categories, and the basic demand quantity vectors include basic demand quantities corresponding to the K product categories, and M, N, and K are all positive integers; S102, determining a comprehensive demand vector based on N basic demand vectors; S103, determining initial priorities corresponding to the K product categories based on the comprehensive demand vector and a plurality of pre-acquired historical demand vectors; S104, obtaining reference priority information set by the user, and determining target priorities corresponding to the K product categories respectively according to the initial priorities corresponding to the K product categories and the reference priority information; S105, for any product category, determining a target mapping function according to the target priority corresponding to the product category; S106, obtaining a transmission distance between each supply side and each demand side, and mapping a reference weight between each supply side and each demand side according to the transmission distance between each supply side and each demand side and the target mapping function; S107, determining transmission information based on the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side, and the reference weight between each supply side and each demand side, wherein the transmission information is used to assist the user in making supply chain decisions.

[0007] The present invention also provides an interactive intelligent decision-making device for a supply chain, the interactive intelligent decision-making device for a supply chain comprising: An information acquisition module is configured to acquire, at a preset time point, supply quantity vectors corresponding to M supply sides and basic demand quantity vectors corresponding to N demand sides, wherein the supply quantity vectors include supply quantities corresponding to K product categories, and the basic demand quantity vectors include basic demand quantities corresponding to the K product categories, and M, N, and K are all positive integers; A vector calculation module is used to determine a comprehensive demand vector based on N basic demand vectors; a priority determination module, configured to determine initial priorities corresponding to the K product categories respectively according to the comprehensive demand vector and a plurality of pre-acquired historical demand vectors; an interactive updating module, configured to obtain reference priority information set by a user, and determine target priorities corresponding to the K product categories respectively according to the initial priorities corresponding to the K product categories and the reference priority information; A function determination module is used to determine a target mapping function for any product category according to the target priority corresponding to the product category; a weight mapping module, configured to obtain a transmission distance between each supply side and each demand side, and map a reference weight between each supply side and each demand side according to the transmission distance between each supply side and each demand side and the target mapping function; The transmission decision module is used to determine the transmission information based on the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side and the reference weight between each supply side and each demand side, wherein the transmission information is used to assist the user in making supply chain decisions.

[0008] The present invention also provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned interactive intelligent decision-making method for the supply chain when executing the computer program.

[0009] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned interactive intelligent decision-making method for the supply chain.

[0010] The present invention has at least the following beneficial effects: by comprehensively analyzing the supply of multiple supply sides and the demand of multiple demand sides, the integration of multi-dimensional information is realized, providing a complete data basis for decision-making, determining the initial priority by combining the demand vector and the historical demand vector, introducing historical data as a quantitative basis, avoiding the subjective bias of relying solely on experience, making the priority division of product categories more in line with the actual supply and demand laws, allowing users to interactively intervene, so that the decision results are better adapted to the actual scenario, dynamically determining the target mapping function for different product categories, and calculating the reference weight in combination with the transmission distance between the supply side and the demand side, so that resource allocation not only considers the supply and demand relationship, but also takes into account actual constraints such as transportation costs, thereby improving the accuracy and flexibility of supply chain decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A flowchart of an interactive intelligent decision-making method for a supply chain provided in the first embodiment of the present invention; Figure 2 This is a structural diagram of an interactive intelligent decision-making device for a supply chain provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0013] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0014] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It is understood that, where appropriate, the above-mentioned terms used to distinguish similar objects can be interchanged so that the present invention can also implement other embodiments other than the above-mentioned illustrated embodiments or described embodiments. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0015] Example 1 This embodiment provides an interactive intelligent decision-making method for supply chain. Figure 1 FIG. 1 is a flow chart of an interactive intelligent decision-making method for a supply chain provided in a first embodiment of the present invention. The interactive intelligent decision-making method for a supply chain includes the following steps: S101, at a preset time point, obtaining supply quantity vectors corresponding to M supply sides and basic demand quantity vectors corresponding to N demand sides, wherein the supply quantity vectors include supply quantities corresponding to K product categories, and the basic demand quantity vectors include basic demand quantities corresponding to the K product categories, and M, N, and K are all positive integers; S102, determining a comprehensive demand vector based on N basic demand vectors; S103, determining initial priorities corresponding to the K product categories based on the comprehensive demand vector and a plurality of pre-acquired historical demand vectors; S104, obtaining reference priority information set by the user, and determining target priorities corresponding to the K product categories respectively according to the initial priorities corresponding to the K product categories and the reference priority information; S105, for any product category, determining a target mapping function according to the target priority corresponding to the product category; S106, obtaining a transmission distance between each supply side and each demand side, and mapping a reference weight between each supply side and each demand side according to the transmission distance between each supply side and each demand side and the target mapping function; S107, determining transmission information based on the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side, and the reference weight between each supply side and each demand side, wherein the transmission information is used to assist the user in making supply chain decisions.

[0016] Among them, the preset time point may refer to the time point when data is collected, the supply side may include product manufacturers, warehouses, etc., and the demand side may include distribution side, retail side, etc.

[0017] The supply quantity may indicate the number of products of the corresponding product category that the supply side can provide at a preset time point, and the basic demand quantity may indicate the number of products of the corresponding product category that the demand side demands at a preset time point.

[0018] The comprehensive demand vector can represent the overall demand information of each product category, and the historical demand vector can represent the overall demand information of each product category at a historical time point.

[0019] The initial priority may refer to the priority of each product category obtained based on the demand information analysis, and the target priority may refer to the priority of each product category determined after the user interaction information is introduced.

[0020] The target mapping function may represent a mapping relationship between a transmission distance and a reference weight, and the transmission distance may refer to a product transportation distance corresponding to a preset time point in the supply side network between a corresponding supply side and a corresponding demand side.

[0021] Transmission information can indicate the quantity of products sent from each supply side to each demand side. Transmission information can assist supply chain managers in making decisions on supply chain transmission plans.

[0022] In a specific embodiment, determining the comprehensive demand vector based on the N basic demand vectors includes: The N basic demand vectors are added element by element to obtain a first addition result, and the first addition result is used as the comprehensive demand vector.

[0023] Among them, the basic demand vector can be represented by a vector of size 1×K. Adding N basic demand vectors element by element can mean that, for any column, the basic demands corresponding to the column in the N basic demand vectors are added to obtain the comprehensive demand corresponding to the column, and K columns are traversed to obtain the comprehensive demands corresponding to K product categories. The comprehensive demands corresponding to K product categories are spliced together to form a comprehensive demand vector of size 1×K.

[0024] In a specific embodiment, determining the initial priorities corresponding to the K product categories respectively according to the comprehensive demand vector and the pre-acquired historical demand vector includes: For any product category, determine the comprehensive demand corresponding to the product category from the comprehensive demand corresponding to the K product categories included in the comprehensive demand vector; Determine the historical demand corresponding to each product category from the historical demand corresponding to the K product categories included in each historical demand vector; The maximum value of all historical demands is used as the reference demand; Calculating a ratio of the comprehensive demand to the reference demand to obtain a ratio calculation result; An initial priority corresponding to the product category is determined based on the ratio calculation result.

[0025] The reference demand may represent the maximum demand of the corresponding product category. Since the magnitude of the demand of each product category is usually not uniform, this embodiment determines the initial priority based on the ratio of the comprehensive demand to the reference demand.

[0026] Specifically, it can be known that the value range of the ratio calculation result is [0,1]. The implementer can preset several ratio intervals, each ratio interval corresponds to an initial priority, and the initial priority corresponding to the ratio interval into which the ratio calculation result of the corresponding product category falls is used as the initial priority of the corresponding product category.

[0027] As an example, the ratio range can be set to [0, 0.3), [0.3, 0.6), [0.6, 0.8), [0.8, 1], where the initial priority corresponding to [0, 0.3) is 1, the initial priority corresponding to [0.3, 0.6) is 2, the initial priority corresponding to [0.6, 0.8) is 3, and the initial priority corresponding to [0.8, 1] is 4. The larger the initial priority, the higher the supply priority of the corresponding product category.

[0028] In a specific embodiment, the reference priority information includes reference priorities corresponding to several product categories; Determining the target priorities corresponding to the K product categories respectively according to the initial priorities corresponding to the K product categories and the reference priority information includes: For any product category, if there is a corresponding reference priority for that product category, the reference priority for that product category will be used as the target priority for that product category; If there is no corresponding reference priority for the product category, the initial priority corresponding to the product category will be used as the target priority corresponding to the product category.

[0029] The user may refer to a supply chain manager. The user may set reference priority information according to the real-time needs of the actual supply chain. The reference priority information may be used to specify reference priorities corresponding to some or all product categories.

[0030] In a specific embodiment, for any product category, determining the target mapping function according to the target priority corresponding to the product category includes: S105, for any product category, mapping the adjustment coefficient value corresponding to the product category according to the target priority corresponding to the product category; S106 , assigning a value to a preset adjustment coefficient in a basic mapping function including the preset adjustment coefficient according to the adjustment coefficient value to obtain the target mapping function.

[0031] Among them, the mapping of the adjustment coefficient value can be implemented in the form of a lookup table. For example, the lookup table can include adjustment coefficient values corresponding to different target priorities. In this embodiment, the value range of the adjustment coefficient value can be (0,1]. The larger the target priority, the larger the adjustment coefficient value.

[0032] Specifically, the basic mapping function in this embodiment adopts y=e -w×x , where x is the transmission distance, w is the preset adjustment coefficient, y is the reference weight, and the transmission distance is a normalized value determined according to the ratio of the current transmission distance to the maximum value of all transmission distances. The preset adjustment coefficient can be used to control the amplitude of the reference weight change when the transmission distance changes. The greater the target priority, the larger the adjustment coefficient value, and the greater the amplitude of the reference weight change corresponding to the fixed transmission distance change. That is, the greater the influence of the transmission distance on the reference weight, indicating that more attention is paid to the transmission distance when setting the reference weight, that is, more attention is paid to the transmission efficiency. It can be seen that the purpose of using a negative exponential function in the basic mapping function of this embodiment is also to make the reference weight of a smaller transmission distance have a greater influence on the reference weight, and to make the reference weight of a larger transmission distance have a smaller influence on the reference weight.

[0033] According to the transmission distance and target mapping function between each supply side and each demand side, after mapping to obtain the reference weight between each supply side and each demand side, the reference weight needs to be adjusted so that the reference weight is an integer, so as to facilitate the subsequent determination of the transmission information based on the reference weight. The adjustment method can be to multiply all reference weights with a specific value so that all multiplication results are integers, and then calculate the greatest common divisor of all multiplication results, and divide all multiplication results by the greatest common divisor respectively to obtain the adjusted reference weight between each supply side and each demand side.

[0034] In a specific embodiment, determining the transmission information according to the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side, and the reference weight between each supply side and each demand side includes: S1071, initializing the basic transmission volume between each demand side and each supply side to zero, and initializing the temporary storage volume corresponding to each supply side to the supply volume corresponding to each supply side; S1072: For any demand side, when the sum of the basic transmission amounts corresponding to the demand side and each supply side is less than the demand amount of the demand side, the basic transmission amounts corresponding to the demand side and each supply side are updated according to the reference weights corresponding to the demand side and each supply side; S1073: updating the temporary storage capacity corresponding to each supply side according to the reference weights corresponding to each demand side and each supply side; S1074, traverse each demand side to obtain the updated basic transmission volume between each demand side and each supply side, and the updated temporary storage volume corresponding to each supply side; S1075: Return to step S1072 and execute until the sum of the basic transmission amounts corresponding to any demand side and each supply side is greater than the demand amount corresponding to the demand side, or the temporary storage amounts corresponding to each supply side are all zero, and the basic transmission amount between each demand side and each supply side is used as the target transmission amount between each demand side and each supply side; S1076 , determining a transmission vector of each supply side according to the target transmission volume between each demand side and each supply side, and using the transmission vector of each supply side as the transmission information.

[0035] Among them, updating the temporary storage capacity corresponding to each supply side according to the basic transmission capacity corresponding to the demand side and each supply side may mean that, for any supply side, the change in the basic transmission capacity between the demand side and the supply side is determined, and the temporary storage capacity corresponding to the supply side is updated by subtracting the change in the basic transmission capacity between the demand side and the supply side from the temporary storage capacity of the demand side and the supply side.

[0036] Specifically, when the sum of the basic transmission volumes corresponding to any demand side and each supply side is greater than the demand corresponding to the demand side, it means that the product demands of all demand sides are met, and the iteration can be stopped. When the temporary storage volumes corresponding to each supply side are all zero, it means that the product quantities of all supply sides have been allocated, and the iteration can also be stopped.

[0037] In a specific embodiment, when the sum of the basic transmission amounts corresponding to the demand side and each supply side is less than the demand amount of the demand side, updating the basic transmission amounts corresponding to the demand side and each supply side according to the reference weights corresponding to the demand side and each supply side includes: When the sum of the basic transmission amounts corresponding to the demand side and each supply side is less than the demand amount of the demand side, calculating the difference between the demand amount and the sum of the basic transmission amounts to obtain a first difference; Calculate the sum of the reference weights corresponding to the demand side and each supply side to obtain the comprehensive weight; If the first difference is greater than or equal to the comprehensive weight, then adding the reference weights corresponding to the demand side to the basic transmission amounts corresponding to the demand side, and updating the basic transmission amounts corresponding to the demand side and each supply side; If the first difference is less than the comprehensive weight, the difference between the comprehensive weight and the first difference is calculated to obtain the second difference. According to the reference weights from large to small, the respective allocation values corresponding to the demand side are determined according to the second difference. The respective allocation values corresponding to the demand side are added to the respective basic transmission amounts corresponding to the demand side, and the basic transmission amounts corresponding to the demand side and the respective supply sides are updated.

[0038] Among them, the comprehensive weight can represent the number of products that can be allocated to the corresponding demand side in a single iteration, and the first difference can represent the number of products required by the corresponding demand side in the current iteration round.

[0039] Specifically, adding the various reference weights corresponding to the demand side to the various basic transmission volumes corresponding to the demand side may mean that, for any supply side, the reference weight between the demand side and the supply side and the basic transmission volume between the demand side and the supply side are added to update the basic transmission volumes corresponding to the demand side and each supply side respectively.

[0040] The second difference may refer to the quantity of products required to be allocated on the demand side when the first difference is less than the comprehensive weight.

[0041] Determining the respective allocation values corresponding to the demand side according to the second difference in descending order of the reference weights may mean taking the second difference as the remaining value, sorting the respective supply sides in descending order of the reference weights to form a supply side sequence, initializing the supply side identifier Q=1, and judging the relationship between the reference weight corresponding to the Qth supply side in the supply side sequence and the remaining value. If the reference weight corresponding to the Qth supply side in the supply side sequence is less than or equal to the remaining value, then determining the allocation value corresponding to the Qth supply side in the supply side sequence as the reference weight corresponding to the Qth supply side, and updating the remaining value by subtracting the reference weight corresponding to the Qth supply side from the remaining value, updating Q=Q+1, and returning to the step of judging the relationship between the reference weight corresponding to the Qth supply side in the supply side sequence and the remaining value. If the reference weight corresponding to the Qth supply side in the supply side sequence is greater than the remaining value, then determining the allocation value corresponding to the Qth supply side in the supply side sequence as the remaining value, and setting the allocation values corresponding to each supply side whose allocation value has not been determined to zero.

[0042] Adding the various allocated values corresponding to the demand side to the various basic transmission volumes corresponding to the demand side, and updating the basic transmission volumes corresponding to the demand side and each supply side respectively, may mean that, for any supply side, adding the allocated value between the demand side and the supply side and the basic transmission volume between the demand side and the supply side, and updating the basic transmission volumes corresponding to the demand side and each supply side respectively.

[0043] In the first embodiment of the present invention, by comprehensively analyzing the supply quantities of multiple supply sides and the demand quantities of multiple demand sides, the integration of multi-dimensional information is achieved, providing a complete data basis for decision-making, and determining the initial priority by combining the comprehensive demand vector and the historical demand vector. By introducing historical data as a quantitative basis, the subjective bias of relying solely on experience is avoided, and the priority division of product categories is more in line with the actual supply and demand laws. Users are allowed to conduct interactive intervention so that the decision results are better adapted to the actual scenario. The target mapping function is dynamically determined for different product categories, and the reference weight is calculated in combination with the transmission distance between the supply side and the demand side, so that resource allocation not only considers the supply and demand relationship, but also takes into account actual constraints such as transportation costs, thereby improving the accuracy and flexibility of supply chain decisions.

[0044] Example 2 This second embodiment provides an interactive intelligent decision-making device for a supply chain, such as Figure 2 FIG. 1 is a schematic diagram of the structure of an interactive intelligent decision-making device for a supply chain provided by a second embodiment of the present invention. The interactive intelligent decision-making device for a supply chain includes: The information acquisition module 201 is configured to acquire, at a preset time point, supply quantity vectors corresponding to M supply sides and basic demand quantity vectors corresponding to N demand sides, wherein the supply quantity vectors include supply quantities corresponding to K product categories, and the basic demand quantity vectors include basic demand quantities corresponding to the K product categories, and M, N, and K are all positive integers. A vector calculation module 202 is used to determine a comprehensive demand vector based on N basic demand vectors; A priority determination module 203 is configured to determine initial priorities corresponding to the K product categories based on the comprehensive demand vector and a plurality of pre-acquired historical demand vectors; The interactive updating module 204 is configured to obtain reference priority information set by the user, and determine target priorities corresponding to the K product categories based on the initial priorities corresponding to the K product categories and the reference priority information; Function determination module 205, for determining a target mapping function for any product category according to the target priority corresponding to the product category; a weight mapping module 206 configured to obtain a transmission distance between each supply side and each demand side, and to map a reference weight between each supply side and each demand side according to the transmission distance between each supply side and each demand side and the target mapping function; The transmission decision module 207 is used to determine the transmission information based on the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side and the reference weight between each supply side and each demand side, wherein the transmission information is used to assist the user in making supply chain decisions.

[0045] It should be noted that the specific limitations of the interactive intelligent decision-making device for a supply chain can be found in the limitations of the interactive intelligent decision-making method for a supply chain described above and will not be further elaborated here. The information interaction and execution process between the aforementioned modules, as well as other aspects, are based on the same concept as the method embodiments of the present invention. Their specific functions and technical effects can be found in the method embodiments and will not be further elaborated here.

[0046] Example 3 This third embodiment provides a computer device, which may be a server. The computer device may include a processor, a memory, a network interface, and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, an interactive intelligent decision-making method for a supply chain is implemented.

[0047] Example 4 This fourth embodiment provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, this computer program implements the interactive intelligent decision-making method for a supply chain described in the aforementioned embodiment. To avoid repetition, this computer program is omitted here. Alternatively, when executed by a processor, this computer program implements the functions of the various modules / units of the aforementioned interactive intelligent decision-making device for a supply chain. To avoid repetition, this computer program is omitted here.

[0048] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0049] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0050] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any form. Although the present invention has been disclosed as above in terms of preferred embodiments, they are not intended to limit the present invention. Any technician familiar with this profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. An interactive intelligent decision-making method for supply chain, characterized in that: The interactive intelligent decision-making method for supply chain includes the following steps: S101, at a preset time point, obtaining supply quantity vectors corresponding to M supply sides and basic demand quantity vectors corresponding to N demand sides, wherein the supply quantity vectors include supply quantities corresponding to K product categories, and the basic demand quantity vectors include basic demand quantities corresponding to the K product categories, and M, N, and K are all positive integers; S102, determining a comprehensive demand vector based on N basic demand vectors; S103, determining initial priorities corresponding to the K product categories based on the comprehensive demand vector and a plurality of pre-acquired historical demand vectors; S104, obtaining reference priority information set by the user, and determining target priorities corresponding to the K product categories respectively according to the initial priorities corresponding to the K product categories and the reference priority information; S105, for any product category, determining a target mapping function according to the target priority corresponding to the product category; S106, obtaining a transmission distance between each supply side and each demand side, and mapping a reference weight between each supply side and each demand side according to the transmission distance between each supply side and each demand side and the target mapping function; S107, determining transmission information based on the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side, and the reference weight between each supply side and each demand side, wherein the transmission information is used to assist the user in making supply chain decisions.

2. The interactive intelligent decision-making method for supply chain according to claim 1, characterized in that: Determining the comprehensive demand vector based on the N basic demand vectors includes: The N basic demand vectors are added element by element to obtain a first addition result, and the first addition result is used as the comprehensive demand vector.

3. The interactive intelligent decision-making method for supply chain according to claim 1, characterized in that: The determining of the initial priorities corresponding to the K product categories according to the comprehensive demand vector and the pre-acquired historical demand vector includes: For any product category, determine the comprehensive demand corresponding to the product category from the comprehensive demand corresponding to the K product categories included in the comprehensive demand vector; Determine the historical demand corresponding to each product category from the historical demand corresponding to the K product categories included in each historical demand vector; The maximum value of all historical demands is used as the reference demand; Calculating a ratio of the comprehensive demand to the reference demand to obtain a ratio calculation result; An initial priority corresponding to the product category is determined based on the ratio calculation result.

4. The interactive intelligent decision-making method for supply chain according to claim 1, characterized in that: The reference priority information includes reference priorities corresponding to several product categories; Determining the target priorities corresponding to the K product categories respectively according to the initial priorities corresponding to the K product categories and the reference priority information includes: For any product category, if there is a corresponding reference priority for that product category, the reference priority for that product category will be used as the target priority for that product category; If there is no corresponding reference priority for the product category, the initial priority corresponding to the product category will be used as the target priority corresponding to the product category.

5. The interactive intelligent decision-making method for supply chain according to claim 1, characterized in that: The target mapping function is determined for any product category according to the target priority corresponding to the product category, including: S105, for any product category, mapping the adjustment coefficient value corresponding to the product category according to the target priority corresponding to the product category; S106 , assigning a value to a preset adjustment coefficient in a basic mapping function including the preset adjustment coefficient according to the adjustment coefficient value to obtain the target mapping function.

6. The interactive intelligent decision-making method for supply chain according to claim 1, characterized in that: The determining of the transmission information according to the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side, and the reference weight between each supply side and each demand side includes: S1071, initializing the basic transmission volume between each demand side and each supply side to zero, and initializing the temporary storage volume corresponding to each supply side to the supply volume corresponding to each supply side; S1072: For any demand side, when the sum of the basic transmission amounts corresponding to the demand side and each supply side is less than the demand amount of the demand side, the basic transmission amounts corresponding to the demand side and each supply side are updated according to the reference weights corresponding to the demand side and each supply side; S1073: updating the temporary storage capacity corresponding to each supply side according to the basic transmission capacity corresponding to each supply side; S1074, traverse each demand side to obtain the updated basic transmission volume between each demand side and each supply side, and the updated temporary storage volume corresponding to each supply side; S1075: Return to step S1072 and execute until the sum of the basic transmission amounts corresponding to any demand side and each supply side is greater than the demand amount corresponding to the demand side, or the temporary storage amounts corresponding to each supply side are all zero, and the basic transmission amount between each demand side and each supply side is used as the target transmission amount between each demand side and each supply side; S1076 , determining a transmission vector of each supply side according to the target transmission volume between each demand side and each supply side, and using the transmission vector of each supply side as the transmission information.

7. The interactive intelligent decision-making method for supply chain according to claim 6, characterized in that: When the sum of the basic transmission amounts respectively corresponding to the demand side and each supply side is less than the demand amount of the demand side, updating the basic transmission amounts respectively corresponding to the demand side and each supply side according to the reference weights respectively corresponding to the demand side and each supply side includes: When the sum of the basic transmission amounts corresponding to the demand side and each supply side is less than the demand amount of the demand side, calculating the difference between the demand amount and the sum of the basic transmission amounts to obtain a first difference; Calculate the sum of the reference weights corresponding to the demand side and each supply side to obtain the comprehensive weight; If the first difference is greater than or equal to the comprehensive weight, then adding the reference weights corresponding to the demand side to the basic transmission amounts corresponding to the demand side, and updating the basic transmission amounts corresponding to the demand side and each supply side; If the first difference is less than the comprehensive weight, the difference between the comprehensive weight and the first difference is calculated to obtain the second difference. According to the reference weights from large to small, the respective allocation values corresponding to the demand side are determined according to the second difference. The respective allocation values corresponding to the demand side are added to the respective basic transmission amounts corresponding to the demand side, and the basic transmission amounts corresponding to the demand side and the respective supply sides are updated.

8. An interactive intelligent decision-making device for a supply chain, characterized in that: The interactive intelligent decision-making device for the supply chain includes: An information acquisition module is configured to acquire, at a preset time point, supply quantity vectors corresponding to M supply sides and basic demand quantity vectors corresponding to N demand sides, wherein the supply quantity vectors include supply quantities corresponding to K product categories, and the basic demand quantity vectors include basic demand quantities corresponding to the K product categories, and M, N, and K are all positive integers; A vector calculation module is used to determine a comprehensive demand vector based on N basic demand vectors; a priority determination module, configured to determine initial priorities corresponding to the K product categories respectively according to the comprehensive demand vector and a plurality of pre-acquired historical demand vectors; an interactive updating module, configured to obtain reference priority information set by a user, and determine target priorities corresponding to the K product categories respectively according to the initial priorities corresponding to the K product categories and the reference priority information; A function determination module is used to determine a target mapping function for any product category according to the target priority corresponding to the product category; a weight mapping module, configured to obtain a transmission distance between each supply side and each demand side, and map a reference weight between each supply side and each demand side according to the transmission distance between each supply side and each demand side and the target mapping function; The transmission decision module is used to determine the transmission information based on the supply quantity corresponding to each supply side under the product category, the demand quantity corresponding to each demand side and the reference weight between each supply side and each demand side, wherein the transmission information is used to assist the user in making supply chain decisions.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the interactive intelligent decision-making method for the supply chain according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the interactive intelligent decision-making method for a supply chain according to any one of claims 1 to 7 is implemented.

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