Method and apparatus for link object resource allocation based on supply chain model

Abstract

This application discloses a method and apparatus for resource allocation of link objects based on a supply chain model. The method includes: determining initial parameters based on an obtained supply chain model; determining target resource data of link objects based on the initial parameters under a target competitive recovery mode in the supply chain model; constructing a first cooperation mode, a second cooperation mode, a third cooperation mode, and a fourth cooperation mode based on the supply chain model; using a reverse-order solving algorithm to determine the first cooperation resource data, the second cooperation resource data, the third cooperation resource data, and the fourth cooperation resource data in the supply chain model under the first cooperation mode, respectively; and determining resource allocation data of link objects based on the target resource data and the four types of cooperation resource data obtained above, so as to solve the technical problem of unbalanced and inefficient resource allocation of link objects in the supply chain model.

Description

Technical Field

[0001] This application relates to the field of supply chain management technology, and in particular to a method and apparatus for allocating link objects based on a supply chain model. Background Technology

[0002] Existing remanufacturing supply chain operation decision-making algorithms mainly revolve around the construction of closed-loop supply chain models and the impact of policy interventions, but they do not incorporate "green innovation" as a core variable into the analysis framework. This leads to a mismatch between the algorithm model and the actual industry, making it impossible to achieve synergistic solutions for green innovation and supply chain operation decisions, and also making it difficult to support enterprises' green innovation investment decisions.

[0003] Existing algorithms for recycling retired batteries mainly focus on building recycling models and designing subsidy incentive models, but they have multiple shortcomings: they do not focus on specific remanufacturing scenarios, resulting in a disconnect between the algorithm logic of recycling and remanufacturing processes; they have not built an algorithm linking green innovation and remanufacturing efficiency; they do not include the "remaining capacity uncertainty" parameter of retired batteries, assuming that battery attributes are deterministic variables, which leads to biased decision-making results and ineffective risk assessment; and they lack practical engineering algorithms, failing to address the pain points of high industry recycling barriers and low levels of collaboration.

[0004] While existing supply chain revenue distribution algorithms cover alliance game distribution in both deterministic and uncertain scenarios, they have significant shortcomings: they fail to incorporate the parameter of "uncertainty of remaining battery capacity," leading to unrealistic allocation solutions; they are disconnected from the parameter of "green innovation contribution," lacking an incentive mechanism that inhibits innovation; they rely excessively on the weight of "marginal contribution" and fail to design logic to protect the interests of weaker members, resulting in the failure of alliance stability assessment; and their single-mode has low generalization, making it unable to support the construction of long-term stable cooperative alliances, thus leading to technical problems such as unbalanced resource allocation among link objects in the supply chain model and low efficiency. Summary of the Invention

[0005] In view of this, the present application provides a method and apparatus for resource allocation of link objects based on a supply chain model, the main purpose of which is to solve the technical problem of unbalanced and inefficient resource allocation of link objects in the supply chain model.

[0006] According to one aspect of this application, a method for resource allocation of link objects based on a supply chain model is provided. The method includes: acquiring a supply chain model in a retired battery remanufacturing scenario, and determining initial parameters based on the supply chain model, wherein the link objects in the supply chain model include at least: manufacturers, retailers, and recyclers; determining target resource data of the link objects based on the initial parameters using a reverse-order solving algorithm when the supply chain model executes a target competitive recycling mode; constructing a first cooperation mode, a second cooperation mode, a third cooperation mode, and a fourth cooperation mode based on the supply chain model, wherein the first cooperation mode involves manufacturers and retailers as partners, the second cooperation mode involves recyclers and manufacturers as partners, the third cooperation mode involves retailers and recyclers as partners, and the fourth cooperation mode involves manufacturers, retailers, and recyclers as partners; determining the first cooperation resource data, the second cooperation resource data, the third cooperation resource data, and the fourth cooperation resource data of the supply chain model under the first cooperation mode, the second cooperation resource data, the third cooperation resource data, and the fourth cooperation resource data respectively using a reverse-order solving algorithm; and determining resource allocation data of the link objects based on the target resource data, the first cooperation resource data, the second cooperation resource data, the third cooperation resource data, and the fourth cooperation resource data using a target allocation algorithm.

[0007] Optionally, the initial parameters may include at least: battery pricing parameters, manufacturer's green innovation capability parameters, retailer's green technology evaluation parameters, manufacturer's green innovation cost, retailer's green technology cost, production cost per unit of new battery, production cost of remanufactured battery, first remanufacturing cost savings per unit of battery, transfer price parameters per unit of retired battery, first recycling price parameters for recyclers, recycling volume of recyclers, and retired battery recycling parameters.

[0008] Optionally, in the target competitive recycling mode of the supply chain model, the target resource data of the link objects is determined based on the initial parameters using a reverse-order solution algorithm. This includes: determining the first initial resource data of the recycler based on the transfer price parameter, the first recycling price parameter, and the recycling volume; determining the first and second sales resource parameters of the retailer based on the initial parameters, and determining the second initial resource data of the retailer based on the first, second, and green technology parameters, wherein the first sales resource parameter is the sales resource parameter for the retailer to sell new batteries, and the second sales resource parameter is the sales resource parameter for the retailer to sell retired batteries; determining the first and second transaction value parameters of the manufacturer, as well as the second remanufacturing cost savings of retired batteries, based on the initial parameters, and determining the third initial resource data of the manufacturer based on the first, second, and second remanufacturing cost savings and green innovation cost, wherein the first transaction value parameter is the transaction value parameter for the manufacturer to wholesale new batteries, and the second transaction value parameter is the transaction value parameter for the manufacturer to wholesale retired batteries; and determining the target resource data based on the first, second, and third initial resource data using a reverse-order solution algorithm.

[0009] Optionally, the target resource data includes at least: first target resource data corresponding to the first initial resource data, second target resource data corresponding to the second initial resource data, and third target resource data corresponding to the third initial resource data. The first target resource data includes, according to the following formula:

[0010] in, Used to represent the first target resource data; A parameter used to indicate the transfer price of a single retired battery; Used to represent the recycling price coefficient; Used to represent the intensity coefficient of recycling competition; The second target resource data includes the following formula:

[0011] in, Used to represent the second target resource data; Used to indicate the production cost per unit of new battery; A price sensitivity coefficient used to represent the sales price of recycled batteries; Cost coefficients used to represent parameters for evaluating green technologies; Cost coefficients used to represent parameters of green innovation capability; Used to represent the green technology evaluation sensitivity coefficient of consumer objects in the link object; A green innovation sensitivity coefficient used to represent the target consumer; The third target resource data includes the following formula:

[0012] in, Used to represent third-target resource data; Used to indicate the cost savings in remanufacturing per unit of recycled battery; Used to indicate the proportion of retired batteries that are reused in a tiered manner; This data represents the manufacturer's unit resource data when retired batteries are transferred to the secondary utilization market.

[0013] Optionally, the first cooperative resource data includes at least: first object resource data and second object resource data, wherein the first object resource data represents the resource data of the manufacturer and retailer constituting the cooperative object, and the second object resource data represents the resource data of the recycler under the first cooperative mode of the supply chain model; the second cooperative resource data includes at least: third object resource data and fourth object resource data, wherein the third object resource data represents the resource data of the recycler and manufacturer constituting the cooperative object, and the fourth object resource data represents the resource data of the retailer under the second cooperative mode of the supply chain model; the third cooperative resource data includes at least: fifth object resource data and sixth object resource data, wherein the fifth object resource data represents the resource data of the retailer and recycler constituting the cooperative object, and the sixth object resource data represents the resource data of the manufacturer under the third cooperative mode of the supply chain model.

[0014] Optionally, the first object resource data includes, according to the following formula:

[0015] in, Used to represent the resource data of the first object;

[0016]

[0017] The second object resource data includes the following formula:

[0018] in, Used to represent resource data of the second object; The third object resource data includes the following formula:

[0019] in, Used to represent resource data of a third object; The fourth object resource data includes the following formula:

[0020] in, Used to represent the resource data of the fourth object; The fifth object resource data includes the following formula:

[0021] in, Used to represent the resource data of the fifth object; The sixth object resource data includes the following formula:

[0022] in, Used to represent the resource data of the sixth object.

[0023] Optionally, the fourth cooperative resource data includes, using the following formula:

[0024] in, Used to represent the fourth cooperative resource data.

[0025] According to another aspect of this application, a link object resource allocation device based on a supply chain model is provided. The device includes: a first determining unit, configured to acquire a supply chain model in a retired battery remanufacturing scenario and determine initial parameters based on the supply chain model, wherein the link objects in the supply chain model include at least: manufacturers, retailers, and recyclers; a second determining unit, configured to determine target resource data of the link objects based on the initial parameters and using a reverse-order solving algorithm under a target competitive recycling mode executed by the supply chain model; and a construction unit, configured to construct a first cooperation mode, a second cooperation mode, a third cooperation mode, and a fourth cooperation mode based on the supply chain model, wherein the first cooperation mode involves manufacturers and retailers as cooperating objects, and the second cooperation mode... The first cooperation model consists of recyclers and manufacturers; the second cooperation model consists of retailers and recyclers; and the third cooperation model consists of manufacturers, retailers, and recyclers. The third determining unit uses a reverse-order solving algorithm to determine the first cooperation resource data in the first cooperation model, the second cooperation resource data in the second cooperation model, the third cooperation resource data in the third cooperation model, and the fourth cooperation resource data in the fourth cooperation model. The fourth determining unit uses a target allocation algorithm to determine the resource allocation data of the link objects based on the target resource data, the first cooperation resource data, the second cooperation resource data, the third cooperation resource data, and the fourth cooperation resource data.

[0026] According to another aspect of this application, a storage medium is provided on which a computer program is stored, which, when executed by a processor, implements the above-described supply chain model-based link object resource allocation method.

[0027] According to another aspect of this application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the program to implement the above-described supply chain model-based link object resource allocation method.

[0028] Using the above technical solution, this application provides a method for resource allocation of link objects based on a supply chain model. The method includes: first, constructing a supply chain model for the remanufacturing of retired batteries, including manufacturers, retailers, and recyclers, to determine the initial parameters of the supply chain model; then, solving for the target resource data of each link object in the supply chain model under the target competitive recycling mode; then, constructing four cooperation modes respectively: manufacturer and retailer, manufacturer and recycler, retailer and recycler, and three-party full alliance, and solving for the corresponding cooperation resource data for each; finally, combining the target resource data of each link object under the target competitive recycling mode with the resource data of each cooperation mode, and determining the final resource allocation data of each link object through a target allocation algorithm. By incorporating green innovation capability parameters and retailer green technology evaluation parameters into the supply chain model, resource allocation is made more aligned with actual industry scenarios, avoiding inefficiencies caused by mismatched operating conditions. Furthermore, the model covers competition and four types of differentiated cooperation modes and designs an adaptive allocation algorithm that balances incentives for innovation contributions with protection of the interests of weaker members. This balances the benefits of each link object and reduces game imbalances, effectively addressing the technical problems of resource allocation imbalance and inefficiency in the supply chain model. This ensures that resource allocation among link objects in the supply chain model remains balanced, achieving the technical effect of improving resource allocation efficiency.

[0029] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This illustration shows a flowchart of a link object resource allocation method based on a supply chain model provided in an embodiment of this application; Figure 2 This illustration shows a structural diagram of a supply chain model implementing a competitive recycling mode according to an embodiment of this application; Figure 3 This illustration shows a structural diagram of the supply chain decision-making sequence for the remanufacturing of retired batteries, as provided in an embodiment of this application. Figure 4 This illustration shows a structural diagram of a supply chain model implementing different cooperation modes according to an embodiment of this application; Figure 5 This illustration shows a schematic diagram of a link object resource allocation device based on a supply chain model, provided in an embodiment of this application. Figure 6 A schematic diagram of the device structure of a computer device provided in an embodiment of this application is shown. Detailed Implementation

[0031] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0032] In this embodiment, Figure 1 This illustration shows a flowchart of a link object resource allocation method based on a supply chain model provided in an embodiment of this application. Figure 1 As shown, the method includes: Step S101: Obtain the supply chain model in the scenario of remanufacturing retired batteries, and determine the initial parameters based on the supply chain model.

[0033] In the technical solution provided by step S101 of this application, a supply chain model in the scenario of remanufacturing retired batteries is obtained, and initial parameters are determined based on the obtained supply chain model. The link objects in the supply chain model include at least: manufacturers, retailers and recyclers.

[0034] Optionally, the manufacturer can be a grid dismantling center, represented by M. The retailer can be a retired battery retailer, represented by R. The recycler can be a third-party recycler, represented by T. The supply chain model can be called a three-tier supply chain system model.

[0035] For example, in the scenario of remanufacturing retired batteries, a three-tier supply chain system model consisting of manufacturers (grid dismantling centers), retired battery retailers, and third-party recyclers is obtained. Then, the initial parameters required for the model are determined, and the initial parameters include at least: battery pricing parameters, green innovation capability parameters, and green technology evaluation parameters.

[0036] Step S102: In the target competition recovery mode of the supply chain model, the target resource data of the link object is determined based on the initial parameters using the reverse order solution algorithm.

[0037] In the technical solution provided in step S102 of this application, after obtaining the supply chain model, the target resource data of the link object is determined by using the reverse order solution algorithm based on the obtained initial parameters under the target competition recovery mode of the supply chain model.

[0038] Optionally, the reverse order solution algorithm refers to solving the problem step by step from back to front in a game where the manufacturer is in control and the retailers and recyclers are following. First, the optimal decision of the followers (retailers and recyclers) is calculated, and then the optimal decision of the leader (manufacturer) is calculated back. Finally, the optimal resource data of all link objects under the competition or cooperation mode is obtained, which ensures the uniqueness and optimality of the solution and provides an accurate basis for subsequent resource allocation.

[0039] Optionally, the target resource data includes at least: first target resource data, second target resource data, and third target resource data. The first target resource data can be referred to as the recycler's optimal resource data or optimal profit data. The second target resource data can be referred to as the retailer's optimal resource data or optimal profit data. The third target resource data can be referred to as the manufacturer's optimal resource data or optimal profit data.

[0040] For example, when the supply chain model is in a competitive recycling mode, based on the initial parameters, the reverse-order solution algorithm outputs the optimal profit data for recyclers, retailers, and manufacturers under this mode.

[0041] Alternatively, the target competitive recycling model can be called the retailer-third-party recycler competitive recycling model, or simply the competitive recycling model. Figure 2 This illustration shows a structural diagram of a supply chain model implementing a competitive recycling mode according to an embodiment of this application. Figure 2 As shown, the competitive recycling model implemented in the supply chain model can include: the virgin materials market, third-party recyclers, manufacturers, retailers, consumers, and retired battery providers.

[0042] Furthermore, the process of using the reverse-order solution algorithm to solve for the target resource data of the link object is as follows: In the forward supply chain algorithm logic, the manufacturer, as the supply chain leader, uses green innovation data such as cathode repair and refunctionalization as the core parameters of the algorithm to conduct algorithm deduction for the core links of retired battery remanufacturing, and outputs the supply parameters of new and remanufactured batteries to retailers; the retailer, as a follower, uses green technology data such as rapid testing and refurbishment technology as algorithm parameters to solve for the algorithm results of battery safety and lifespan optimization, and outputs battery sales parameters to the consumer market. In the reverse supply chain algorithm logic, a competitive recycling algorithm module is constructed between retailers and third-party recyclers. Both recycle retired batteries from consumers and transfer them all to the manufacturer. The algorithm outputs the competitive decision parameters of recycling volume and recycling price for both parties; the manufacturer designs a graded processing algorithm for the remaining capacity of retired batteries, refurbishing high-capacity batteries into recycled batteries and re-entering the consumer market, and dismantling low-capacity batteries to extract materials such as lithium, nickel, and cobalt for secondary use. At the same time, a revenue calculation algorithm is designed for the resale of secondary-use materials back to the primary material market.

[0043] Step S103: Based on the supply chain model, construct the first cooperation model, the second cooperation model, the third cooperation model, and the fourth cooperation model.

[0044] In the technical solution provided in step S103 of this application, a first cooperation mode, a second cooperation mode, a third cooperation mode and a fourth cooperation mode are constructed based on the obtained supply chain model.

[0045] Optionally, the first cooperation model consists of manufacturers and retailers, the second cooperation model consists of recyclers and manufacturers, the third cooperation model consists of retailers and recyclers, and the fourth cooperation model consists of manufacturers, retailers, and recyclers.

[0046] Optionally, the first cooperation mode can be represented by mode MR, which can also be called the MR mode. The second cooperation mode can be represented by mode MT, which can also be called the MT mode. The third cooperation mode can be represented by mode RT, which can also be called the RT mode. The fourth cooperation mode can be called the industry alliance mode, which can be represented by mode MRT, which can also be called the MRT mode.

[0047] For example, based on the obtained three-level supply chain system model, model MR, model MT, model RT, and model MRT are constructed.

[0048] Step S104: Using the reverse order solution algorithm, determine the first cooperative resource data of the supply chain model under the first cooperative mode, the second cooperative resource data under the second cooperative mode, the third cooperative resource data under the third cooperative mode, and the fourth cooperative resource data under the fourth cooperative mode.

[0049] In the technical solution provided in step S104 of this application, after obtaining the four cooperation modes, the reverse order solution algorithm is used to determine the first cooperation resource data, the second cooperation resource data, the third cooperation resource data, and the fourth cooperation resource data of the supply chain model under the four cooperation modes.

[0050] For example, when the supply chain model is implementing the first cooperation mode, manufacturer M and retailer R are considered as a joint entity. The optimal parameters for their shared green innovation capability, green technology evaluation, product retail price, and recycling price are simultaneously calculated to maximize the alliance's total profit. These optimal joint parameters are then used as known inputs and substituted into the profit function of the third-party recycler T to solve for the recycler T's optimal recycling price. Finally, the obtained decision variables are substituted back into the profit functions of each party, outputting the first cooperation resource data under the MR mode. Other MT, RT, and MRT modes follow the same logic.

[0051] It is understood that this is only a preferred implementation method for determining the first cooperative resource, the second cooperative resource data, the third cooperative resource data, and the fourth cooperative resource data, and no specific limitation is made on the method and process of determining the first cooperative resource, the second cooperative resource data, the third cooperative resource data, and the fourth cooperative resource data.

[0052] Step S105: Based on the target resource data, the first cooperative resource data, the second cooperative resource data, the third cooperative resource data, and the fourth cooperative resource data, the resource allocation data of the link object is determined using the target allocation algorithm.

[0053] In the technical solution provided in step S105 of this application, the target resource data, the first cooperative resource data, the second cooperative resource data, the third cooperative resource data and the fourth cooperative resource data obtained above are used to achieve the purpose of determining the resource allocation data of the link object by using the target allocation algorithm.

[0054] For example, based on resource data under the competition mode and four cooperation modes, the target allocation algorithm is used to comprehensively evaluate the expected marginal contribution of each link object in different alliance combinations, and weight parameters are introduced to give basic participation rewards to weaker members, thereby outputting the final resource allocation data that takes into account both allocation fairness and alliance stability, namely the resource allocation data of manufacturers, retailers and recyclers.

[0055] Optionally, the target allocation algorithm can be either a first allocation algorithm (expected Shapley value allocation algorithm) or a second allocation algorithm (expected Solidarity value allocation algorithm). The resource allocation data for the link object includes the manufacturer's resource allocation data, the retailer's resource allocation data, and the recycler's resource allocation data. The manufacturer's resource allocation data can be referred to as the manufacturer's revenue. The retailer's resource allocation data can be referred to as the retailer's revenue. The recycler's resource allocation data can be referred to as the recycler's revenue.

[0056] Optionally, when the target allocation algorithm is the desired Shapley value allocation algorithm, the manufacturer's resource allocation data is obtained through... This is represented. Retailer resource allocation data is presented through... This is represented. The recycler's resource allocation data is presented through... This is represented. When the target allocation algorithm is the desired Solidarity value allocation algorithm, the manufacturer's resource allocation data is represented through... This is represented. Retailer resource allocation data is presented through... This is represented. The recycler's resource allocation data is presented through... To express.

[0057] In this application embodiment, the following uncertain coalition game is defined. ,in, Used to represent the set of all supply chain members. (Allowing the alliance) yes A subset of, for any union , Used to represent the alliance The total benefit obtained through cooperation is represented by the symbol... or Representing the Alliance The cardinality of the set abbreviated as Based on the equilibrium solutions obtained in the above steps under different modes, the characteristic function of each coalition can be obtained. Table 1 is the coalition characteristic function table, as shown in Table 1. The characteristic function used to represent the alliance as retailer R. The characteristic function used to represent the alliance is that of manufacturer M. The characteristic functions of other alliances are shown in Table 1, and will not be repeated here.

[0058] Table 1. Characteristic Functions of the Alliance

[0059] Furthermore, the allocation algorithm design includes two types of revenue allocation algorithms: the expected Shapley value allocation algorithm and the expected Solidarity value allocation algorithm. Each algorithm has its own emphasis on axiomatic properties, and their applicability is dynamically adjusted according to the supply chain scenario. Table 2 compares the axiomatic properties of the two allocation mechanisms, and the algorithmic analysis of their axiomatic properties is shown in Table 2. Table 2 Comparison of the axiomatic properties of the two allocation mechanisms

[0060] For uncertain alliance games The payment by the player is dimensional vector The person in the game The payment received is In uncertain coalition games, the value (also known as the allocation rule) is defined in... A mapping on , A person involved In the game The payment obtained. In order to formulate reasonable distribution rules to maintain the stability of cooperation among members in the game, the expected Shapley value is introduced, let For any The expected Shapley value is expressed as:

[0061] in, Called an insider Against the alliance The expected marginal contribution.

[0062] Furthermore, based on the definitions of Solidarity and expected Shapley value, we obtain the representation of the expected Solidarity value in uncertain coalition games. Let... For any The expected Solidarity value is expressed as:

[0063] in, Called an insider Against the alliance The average expected marginal contribution.

[0064] Based on the above algorithm derivation, the specific calculation formulas for the two types of profit distribution algorithms are shown below:

[0065]

[0066]

[0067] The above formulas yield the allocated benefits for each entity under different allocation algorithms. The two algorithms have different focuses and are suitable for different situations. In the Expected Shapley Value Allocation Algorithm, the manufacturer's benefits far exceed those of retailers and third parties, while in the Expected Solidarity Value Allocation Algorithm, although the gap remains, it has narrowed significantly. Therefore, the Expected Solidarity Value Allocation Algorithm can balance the interests of supply chain members and is more suitable for the early stages of recycling operations, while the Expected Shapley Value Allocation Algorithm tends to focus more on the actual marginal contribution of members and is suitable for more mature recycling supply chains.

[0068] In the technical solutions provided by steps S101 to S105 of this application, a supply chain model for the remanufacturing of retired batteries, including manufacturers, retailers, and recyclers, is first constructed to determine the initial parameters of the supply chain model. Then, the target resource data of each link object in the supply chain model under the target competitive recycling mode is solved. Next, four cooperation modes are constructed, namely, manufacturer and retailer, manufacturer and recycler, retailer and recycler, and three-party full alliance, and the corresponding cooperation resource data is solved for each. Finally, the target resource data of each link object under the target competitive recycling mode is combined with the resource data of each cooperation mode, and the final resource allocation data of each link object is determined by the target allocation algorithm. By incorporating green innovation capability parameters and retailer green technology evaluation parameters into the supply chain model, resource allocation is made more aligned with actual industry scenarios, avoiding inefficiencies caused by mismatched operating conditions. Furthermore, the model covers competition and four types of differentiated cooperation modes and designs an adaptive allocation algorithm that balances incentives for innovation contributions with protection of the interests of weaker members. This balances the benefits of each link object and reduces game imbalances, effectively addressing the technical problems of resource allocation imbalance and inefficiency in the supply chain model. This ensures that resource allocation among link objects in the supply chain model remains balanced, achieving the technical effect of improving resource allocation efficiency.

[0069] The method described in this embodiment will be further described below.

[0070] As an optional implementation method, the initial parameters include at least: battery pricing parameters, manufacturer's green innovation capability parameters, retailer's green technology evaluation parameters, manufacturer's green innovation cost, retailer's green technology cost, production cost per unit of new battery, production cost of remanufactured battery, first remanufacturing cost savings per unit of battery, transfer price parameters per unit of retired battery, recycler's first recycling price parameters, recycler's recycling volume, and retired battery recycling parameters.

[0071] In this embodiment, the battery pricing parameter can be referred to as the battery price, through... p This is expressed as follows. The green innovation capability parameter can be called the green innovation level parameter, or simply the green innovation level, and is expressed through... g This is expressed as follows. Green technology evaluation parameters can be called green technology level parameters, or simply green technology level, and are expressed through... k The production cost per unit of new battery is expressed as follows: The production cost of remanufactured batteries is expressed as follows: This is represented. The first remanufacturing cost savings per unit battery are achieved through... It is expressed as follows, and obtained using the following formula: .

[0072] Optionally, the transfer price parameter per unit of retired battery is represented by 'b', indicating the transfer price per unit of retired battery, transferred from the recycling entity to the manufacturer. The recycler's initial recycling price parameter can be referred to as the recycling price offered by a third-party recycler, through... This is expressed as follows. The amount of retired batteries recycled by a recycler can be referred to as the amount of retired batteries recycled by a third-party recycler, through... This is expressed as follows. The parameters for retired battery recycling can be referred to as the retired battery recycling volume, which is expressed through... To express.

[0073] Optionally, the initial parameters also include: the market demand for new batteries. The market demand for new batteries is determined based on battery pricing parameters, green innovation level parameters, and green technology level parameters, and the above process is expressed by the following formula:

[0074] in, D Used to indicate the market demand for new batteries. A price sensitivity coefficient used to represent the sales price of regenerated batteries. A green innovation sensitivity coefficient used to represent consumers of recycled batteries. This is used to represent the sensitivity of recycled battery consumers to the level of green technology offered by retailers. Because the market for recycled batteries is a startup market, the total amount of retired batteries recycled ( Q ) is far less than the market demand for new batteries ( D ),Right now D > Q Market demand for new batteries D It is a linear function, affected by battery prices. p Retailers' level of green technology k With the level of green innovation of manufacturers gThe impact is determined by setting the potential market size to 1, meaning the demand for new batteries can be obtained using the formula above.

[0075] Optionally, the green innovation cost for manufacturers can be determined using green innovation capability parameters. The green technology cost for retailers can be determined using green technology evaluation parameters. For example, the relationship between the green innovation cost and the green innovation level of battery manufacturers follows a quadratic function, i.e., the green innovation cost is... Furthermore, the relationship between the retailer's green technology costs and green technology evaluation parameters also exhibits a quadratic function, with the retailer's green technology costs being... .in, Cost coefficient used to represent the level of green innovation. Cost coefficient used to represent the level of green technology.

[0076] Optionally, due to the uncertainty of the remaining capacity of retired batteries, it is assumed that the proportion of batteries with lower remaining capacity is... This refers to the proportion of recycled retired batteries that can be used for secondary applications. If it is an uncertain variable, then Used to represent a regular uncertain distribution, and inverse function Yes. Regenerated batteries can save production costs; let's set the cost savings per unit of battery remanufacturing as... To ensure that battery manufacturers have retired batteries for recycling and reuse, it is necessary to meet the cost savings per unit of recycled battery in remanufacturing. The unit revenue that can be obtained when retired batteries are transferred to the secondary utilization market ( The transfer price of recycled batteries shall not be lower than the transfer price of recycled batteries. ,Right now , .in, This term refers to the unit revenue that manufacturers can obtain when retired batteries are transferred to the secondary utilization market; it is simply called unit revenue.

[0077] Alternatively, third-party recyclers are the main players in the retired battery market. With industry development and increased market awareness of resource recycling, retailers are also gradually entering the recycling field, competing with third-party recyclers. For example, a shopping mall might set up battery recycling points in its physical stores, offering subsidies for trade-ins, directly competing with other third-party companies' mall recycling counters in terms of recycling prices and convenience. Recycling volume is a function of recycling price; that is, the higher the recycling price, the greater the recycling volume. The negative impact of competition is denoted as... The amount of retired batteries recycled is expressed by the following formula:

[0078] in, C is used to represent the main entity in the supply chain. Used to represent the price sensitivity coefficient of recycling. Used to represent the recycling competition intensity coefficient, and This means that the recycling price sensitivity coefficient is greater than the recycling competition intensity coefficient, which indicates that the recycling price offered by oneself has a greater impact on the recycling volume than the recycling price offered by competitors. Used to represent the main body j The given recycling price is... Used to represent the main body z The given recycling price.

[0079] Furthermore, under the premise of meeting the same application standards, the new product and the remanufactured product can be considered approximately equivalent in quality and performance. In order to simplify the analysis and focus on the core impact of green innovation and cooperation models, the new product and the remanufactured product in this application are set to have the same price in the market. P To proceed with the sale, and to ensure the existence of a unique equilibrium solution in the model, assume... .

[0080] As an optional implementation, in the target competitive recycling mode of the supply chain model, the target resource data of the link objects is determined based on initial parameters using a reverse-order solving algorithm. This includes: determining the first initial resource data of the recycler based on the transfer price parameter, the first recycling price parameter, and the recycling volume; determining the first and second sales resource parameters of the retailer based on the initial parameters, and determining the second initial resource data of the retailer based on the first, second, and green technology costs, wherein the first sales resource parameter is the sales resource parameter for the retailer to sell new batteries, and the second sales resource parameter is the sales resource parameter for the retailer to sell retired batteries; determining the first and second transaction value parameters of the manufacturer, as well as the second remanufacturing cost savings of retired batteries, based on the initial parameters, and determining the third initial resource data of the manufacturer based on the first, second, and second remanufacturing cost savings and green innovation costs, wherein the first transaction value parameter is the transaction value parameter for the manufacturer to wholesale new batteries, and the second transaction value parameter is the transaction value parameter for the manufacturer to wholesale retired batteries; and determining the target resource data based on the first, second, and third initial resource data using a reverse-order solving algorithm.

[0081] In this embodiment, under a competitive recycling model between retailers and third-party recyclers, the manufacturer, as the leader in the supply chain, needs to determine the wholesale price of the batteries when making decisions. and green innovation level Followers are retailers and third-party recyclers who make decisions simultaneously, each determining the retail price of the battery. Green technology level k The recycling price offered by retailers and the recycling price offered by third-party recyclers. Figure 3 This illustration shows a structural diagram of the supply chain decision-making sequence for the remanufacturing of retired batteries according to an embodiment of this application. Figure 3 As shown, the first stage involves leaders making leading decisions, such as manufacturers determining the wholesale price of batteries and the level of green innovation in recycled batteries; the second stage involves followers making decisions simultaneously, such as retailers determining the retail price of batteries, the level of green technology, and the recycling price, and recyclers also determining the recycling price.

[0082] Optionally, in the target competitive recycling mode of the supply chain model, the recycler's initial resource data is determined based on the transfer price parameter, the first recycling price parameter, and the recycling volume using the following formula, including:

[0083] in, Used to represent the first initial resource data, which may be referred to as the recycler's profit data; Used to indicate the recycling price offered by a third-party recycler; This represents the amount of retired batteries recycled by the recycler, i.e., the amount of retired batteries recycled by the third-party recycler. For example, if the model is constructed and solved using the reverse solution method, the profit function of the third-party recycler consists of the revenue generated by the recycler from selling retired batteries to the battery manufacturer, which is obtained through the above formula.

[0084] Optionally, based on the initial parameters, the retailer's first and second sales resource parameters are determined using the following formula, and based on the first and second sales resource parameters and the green technology cost, the retailer's second initial resource data is determined, including:

[0085] in, Retail price of batteries; Used to indicate the recycling price offered by the retailer; Used to indicate the amount of retired batteries recycled by retailers; Used to represent the second initial resource data, which is used to represent the retailer's profit data.

[0086] Furthermore, the first sales resource parameter represents the revenue generated by the retailer from selling new batteries to consumers. The second sales resource parameter represents the revenue generated by the retailer from selling retired batteries to consumers. For example, the retailer's profit function is determined by the revenue generated by the retailer from selling new batteries to consumers. Revenue from the sale of retired batteries Remove retailer green technology costs constitute.

[0087] Optionally, based on the initial parameters, the manufacturer's first transaction value parameter, second transaction value parameter, and second remanufacturing cost savings of the retired batteries are determined using the following formula. Furthermore, based on the first transaction value parameter, second transaction value parameter, second remanufacturing cost savings, and green innovation cost, the manufacturer's third initial resource data is determined, including:

[0088] in, The third initial resource data, used to represent the battery manufacturer's expected profit, is obtained through a function representing the battery manufacturer's expected profit, i.e., expressed as the manufacturer's profit data, and is obtained through... To represent; Used to indicate the total amount of retired batteries recycled, and .

[0089] Furthermore, the first transaction value parameter represents the revenue generated by the manufacturer wholesaling batteries to retailers. The second transaction value parameter represents the revenue generated by the manufacturer transferring retired batteries to the secondary market. For example, the battery manufacturer's expected profit function is based on the revenue generated by the manufacturer wholesaling batteries to retailers. The revenue generated from reusing retired batteries in the secondary market The cost savings from the remanufacturing of retired batteries And the green innovation costs for battery manufacturers composition.

[0090] As an optional embodiment, the target resource data includes at least: first target resource data corresponding to the first initial resource data, second target resource data corresponding to the second initial resource data, and third target resource data corresponding to the third initial resource data. The first target resource data includes, according to the following formula:

[0091] in, Used to represent the first target resource data; A parameter used to indicate the transfer price of a single retired battery; Used to represent the recycling price coefficient; Used to represent the intensity coefficient of recycling competition; The second target resource data includes the following formula:

[0092] in, Used to represent the second target resource data; Used to indicate the production cost per unit of new battery; A price sensitivity coefficient used to represent the sales price of recycled batteries; Cost coefficients used to represent parameters for evaluating green technologies; Cost coefficients used to represent parameters of green innovation capability; Used to represent the green technology evaluation sensitivity coefficient of consumer objects in the link object; A green innovation sensitivity coefficient used to represent the target consumer; The third target resource data includes the following formula:

[0093] in, Used to represent third-target resource data; Used to indicate the cost savings in remanufacturing per unit of recycled battery; Used to indicate the proportion of retired batteries that are reused in a tiered manner; This data represents the manufacturer's unit resource data when retired batteries are transferred to the secondary utilization market.

[0094] In this embodiment, the profit function obtained in the above steps is optimized by the reverse solution algorithm, and the optimal solution parameters of each entity in the supply chain model under the target competitive recovery mode are output, as shown in Table 3. Table 3 is the optimal profit parameter table of each entity.

[0095] Table 3 Optimal Profit Statement for Each Entity

[0096] As shown in Table 3, the total profit of the supply chain is the sum of the profits of the manufacturer, the retailer, and the recycler.

[0097] As an optional embodiment, the first cooperative resource data includes at least: first object resource data and second object resource data, wherein the first object resource data represents the resource data of the manufacturer and retailer constituting the cooperative object, and the second object resource data represents the resource data of the recycler under the first cooperative mode of the supply chain model; the second cooperative resource data includes at least: third object resource data and fourth object resource data, wherein the third object resource data represents the resource data of the recycler and manufacturer constituting the cooperative object, and the fourth object resource data represents the resource data of the retailer under the second cooperative mode of the supply chain model; the third cooperative resource data includes at least: fifth object resource data and sixth object resource data, wherein the fifth object resource data represents the resource data of the retailer and recycler constituting the cooperative object, and the sixth object resource data represents the resource data of the manufacturer under the third cooperative mode of the supply chain model.

[0098] In this embodiment, the first cooperative resource data includes at least: first object resource data and second object resource data. The first object resource data represents the optimal profit generated by a cooperative partnership between a manufacturer and a retailer, and is obtained through... This is represented. The second object resource data is used to represent the optimal profit generated by the recycler under the MR model, and is expressed through... To express.

[0099] Optionally, the second cooperative resource data includes at least: third object resource data and fourth object resource data, wherein the third object resource data is used to represent the optimal profit generated by the cooperative partnership between recyclers and manufacturers, and through... The fourth object, resource data, is used to represent the optimal profit generated by the retailer under the MT model.

[0100] Optionally, the third cooperative resource data includes at least: fifth object resource data and sixth object resource data, wherein the fifth object resource data is used to represent the optimal profit generated by the cooperative partnership consisting of retailers and recyclers, and through... The sixth object resource data is used to represent the optimal profit generated by the manufacturer in RT mode, through... To express.

[0101] As an optional embodiment, the first object resource data includes, according to the following formula:

[0102] in, Used to represent the resource data of the first object;

[0103]

[0104] The second object resource data includes the following formula:

[0105] in, Used to represent resource data of the second object; The third object resource data includes the following formula:

[0106] in, Used to represent resource data of a third object; The fourth object resource data includes the following formula:

[0107] in, Used to represent the resource data of the fourth object; The fifth object resource data includes the following formula:

[0108] in, Used to represent the resource data of the fifth object; The sixth object resource data includes the following formula:

[0109] in, Used to represent the resource data of the sixth object.

[0110] In this embodiment, moderate competition can stimulate innovation in recycling technology and services through algorithm parameters, thereby enhancing industry vitality. However, to achieve the optimal solution, a cooperation mode algorithm module needs to be designed to reduce the negative impact of competition. Based on the competitive recycling mode implemented in the supply chain model, this algorithm constructs an algorithm model for four differentiated cooperation modes among supply chain members, achieving algorithmic improvement in resource allocation optimization and recycling efficiency, as follows: Figure 4 As shown. Figure 4 This illustration shows a structural diagram of a supply chain model implementing different cooperation modes according to an embodiment of this application, wherein... Figure 4 (a) A structural diagram used to represent the supply chain model execution mode (MR) Figure 4 (b) A structural diagram used to represent the supply chain model execution mode (MT). Figure 4 (c) A structure diagram used to represent the execution mode RT of the supply chain model, and Figure 4 (d) A structural diagram used to represent the Supply Chain Model Execution Mode (MRT).

[0111] Optionally, the structure for implementing the MR pattern in the supply chain model is as follows: Figure 4 As shown in (a), a joint decision-making algorithm module is designed to simultaneously solve for the optimal parameters of green innovation level, green technology level, product retail price, and recycling price. Then, using these parameters as input, the optimal parameters for the recycling price of the third-party recycler are solved. Through the reverse-order solution algorithm, the optimal profit for each entity in the supply chain under the MR model can be obtained as follows:

[0112]

[0113] Based on the optimal profit of the MR alliance and the recycler T obtained above, the total profit of the supply chain under the MR model can be determined. That is, the total profit of the supply chain is equal to the sum of the profits of the two entities. Therefore, the optimal total profit of the supply chain under the MR model is:

[0114] in, Used to represent the optimal total profit of the supply chain under the MR model.

[0115] Alternatively, the supply chain model can implement the MT pattern structure as follows: Figure 4 As shown in (b), a joint decision-making algorithm module is designed to simultaneously solve for the optimal parameters of green innovation level, recycling price, and battery wholesale price. Then, using these parameters as input, the optimal parameters for retail price, green technology level, and battery recycling price are solved. Through a reverse-order solution algorithm, the optimal profit for each entity in the supply chain under the MT model is obtained as follows:

[0116] Based on the optimal profit of the MT alliance and retailer R obtained above, the total profit of the supply chain under the MT model can be determined. That is, the total profit of the supply chain is equal to the sum of the profits of the two entities. Therefore, the optimal total profit of the supply chain under the MT model is:

[0117] in, Used to represent the optimal total profit of the supply chain under the MT model.

[0118] Alternatively, the supply chain model can be implemented using the RT (Real-Time) pattern, as shown below. Figure 4As shown in (c), the manufacturer first uses an algorithm to solve for the optimal parameters of battery wholesale price and green innovation level. Then, using these parameters as input, a joint decision-making algorithm module for retailers and third-party recyclers is designed to simultaneously solve for the optimal parameters of retail price, green technology level, and battery recycling price. By solving the algorithm in reverse order, the optimal profit for each entity in the supply chain under the RT model is obtained as follows:

[0119]

[0120] Based on the optimal profit of the RT alliance and manufacturer M obtained above, the total profit of the supply chain under the RT model can be determined. That is, the total profit of the supply chain is equal to the sum of the profits of the two entities. Therefore, the optimal total profit of the supply chain under the RT model is:

[0121] in, This is used to represent the optimal total profit of the supply chain under the RT (Real-Time) model.

[0122]

[0123] As an optional embodiment, the fourth collaborative resource data includes, according to the following formula:

[0124] in, Used to represent the fourth cooperative resource data.

[0125] In this embodiment, the structure of the supply chain model executing the MRT pattern is as follows: Figure 4 As shown in (d), a joint decision-making algorithm module for the entire alliance of manufacturers, third-party recyclers, and retailers is designed. This module uses the recycling input, green innovation input, and green technology input of the three parties as joint algorithm parameters to simultaneously solve for the optimal decision parameters across the entire chain. Through the reverse-order solution algorithm, the optimal profit of the supply chain under the MRT model is obtained as follows:

[0126] in, This is used to represent the fourth cooperative resource data, which is the optimal profit of the supply chain under the MRT model.

[0127] In this embodiment of the application, when the supply chain model is executed in MR mode, MT mode, RT mode, and MRT mode, the calculation and analysis show that the green innovation level of battery manufacturers has the following relationship: In other words, the supply chain model exhibits the highest level of green innovation under the MRT (Maintenance, Resilience, and Resilience) model, with the MR (Mutual Resilience) model having the same level of green innovation as the MRT model. The green technology levels of retailers are related as follows: In other words, the green technology level of retailers is highest under the MRT (Maintenance, Responsibility, and Technology) model, and equal under the MR (Mutual Responsibility) and RT (Responsibility) models. The green technology level is second highest under the MT (Metal, Material, and Mineral) model, and equal under the MT and RT models. The MRT (Maintenance, Responsibility, and Technology) model has the highest levels of green innovation and green technology, generating the greatest supply chain benefits. Therefore, member companies in the supply chain should actively seek cross-industry cooperation to build industry alliances with shared benefits and strong synergy, maximizing green innovation across the entire supply chain and promoting their own sustainable development.

[0128] Furthermore, as Figure 1 The specific implementation of the method, Figure 5 This illustration shows a structural diagram of a link object resource allocation device based on a supply chain model, as provided in an embodiment of this application. Figure 5 As shown, the link object resource allocation device 500 based on the supply chain model includes: a first determining unit 501, a second determining unit 502, a constructing unit 503, a third determining unit 504, and a fourth determining unit 505.

[0129] The first determining unit 501 is used to obtain a supply chain model in the scenario of remanufacturing retired batteries, and to determine initial parameters based on the supply chain model. The link objects in the supply chain model include at least: manufacturers, retailers and recyclers.

[0130] The second determining unit 502 is used to determine the target resource data of the link object based on the initial parameters and using the reverse order solving algorithm in the target competition recovery mode of the supply chain model.

[0131] Building unit 503 is used to build a first cooperation model, a second cooperation model, a third cooperation model and a fourth cooperation model based on the supply chain model. In the first cooperation model, the manufacturers and retailers are the partners; in the second cooperation model, the recyclers and manufacturers are the partners; in the third cooperation model, the retailers and recyclers are the partners; and in the fourth cooperation model, the manufacturers, retailers and recyclers are the partners.

[0132] The third determining unit 504 is used to determine the first cooperative resource data, the second cooperative resource data, the third cooperative resource data, and the fourth cooperative resource data of the supply chain model under the first cooperative mode, the second cooperative resource data, the third cooperative resource data, and the fourth cooperative resource data under the fourth cooperative mode, respectively, by using the reverse order solving algorithm.

[0133] The fourth determining unit 505 is used to determine the resource allocation data of the link object based on the target resource data, the first cooperative resource data, the second cooperative resource data, the third cooperative resource data and the fourth cooperative resource data, using the target allocation algorithm.

[0134] In this embodiment, a first determining unit acquires a supply chain model in the scenario of remanufacturing retired batteries and determines initial parameters based on the supply chain model. A second determining unit, under the target competitive recycling mode of the supply chain model, determines the target resource data of the link objects based on the initial parameters using a reverse solving algorithm. A construction unit constructs a first cooperation mode, a second cooperation mode, a third cooperation mode, and a fourth cooperation mode based on the supply chain model. A third determining unit, using a reverse solving algorithm, determines the first cooperation resource data of the supply chain model under the first cooperation mode, the second cooperation resource data under the second cooperation mode, the third cooperation resource data under the third cooperation mode, and the fourth cooperation resource data under the fourth cooperation mode. A fourth determining unit, based on the target resource data, the first cooperation resource data, the second cooperation resource data, the third cooperation resource data, and the fourth cooperation resource data, determines the resource allocation data of the link objects using a target allocation algorithm. This effectively solves the technical problem of unbalanced and inefficient resource allocation of link objects in the supply chain model, ensuring that the resource allocation of link objects in the supply chain model remains balanced, thereby improving the technical effect of resource allocation efficiency.

[0135] It should be noted that other corresponding descriptions of the functional units involved in the supply chain model-based link object resource allocation device provided in this application embodiment can be found in the following references. Figure 1 The corresponding descriptions in the methods will not be repeated here.

[0136] This application also provides a computer device, which may specifically be a personal computer, a server, a network device, etc. Figure 6 This application provides a schematic diagram of the device structure of a computer device according to an embodiment of the present application. Figure 6As shown, the computer device includes a bus, a processor, memory, and a communication interface, and may also include an input / output interface and a display device. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores location information. The network interface allows communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the various method embodiments.

[0137] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0138] In one embodiment, a computer-readable storage medium is provided, which may be non-volatile or volatile, having stored thereon a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0139] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0140] It should be noted that the user personal information involved in the embodiments of this application is all authorized (with the knowledge and consent) by the relevant parties or fully authorized by all parties, and the executing entity can obtain it through various legal and compliant means. The collection, storage, use, processing, transmission, provision, and disclosure of the information, data, and signals involved all comply with the relevant laws and regulations of the relevant countries and regions, and do not violate public order and good morals. It should be noted that if any software tools or components other than those of this company appear in the embodiments of this application, they are merely illustrative examples and do not represent actual use.

[0141] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0142] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0143] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for allocating link objects based on a supply chain model, characterized in that, The method includes: Obtain a supply chain model in the scenario of remanufacturing retired batteries, and determine initial parameters based on the supply chain model, wherein the link objects in the supply chain model include at least: manufacturers, retailers and recyclers; In the target competitive recovery mode of the supply chain model, the target resource data of the link object is determined based on the initial parameters using a reverse order solution algorithm; Based on the aforementioned supply chain model, a first cooperation model, a second cooperation model, a third cooperation model, and a fourth cooperation model are constructed. In the first cooperation model, the manufacturer and the retailer constitute the cooperation partners. In the second cooperation model, the recycler and the manufacturer constitute the cooperation partners. In the third cooperation model, the retailer and the recycler constitute the cooperation partners. In the fourth cooperation model, the manufacturer, the retailer, and the recycler constitute the cooperation partners. Using the reverse order solution algorithm, the first cooperative resource data of the supply chain model in the first cooperative mode, the second cooperative resource data in the second cooperative mode, the third cooperative resource data in the third cooperative mode, and the fourth cooperative resource data in the fourth cooperative mode are determined respectively. Based on the target resource data, the first cooperative resource data, the second cooperative resource data, the third cooperative resource data, and the fourth cooperative resource data, the resource allocation data of the link object is determined using a target allocation algorithm.

2. The method according to claim 1, characterized in that, The initial parameters include at least: battery pricing parameters, the manufacturer's green innovation capability parameters, the retailer's green technology evaluation parameters, the manufacturer's green innovation cost, the retailer's green technology cost, the production cost per unit of new battery, the production cost of remanufactured battery, the first remanufacturing cost savings per unit of battery, the transfer price parameter per unit of retired battery, the recycler's first recycling price parameter, the recycler's recycling volume, and retired battery recycling parameters.

3. The method according to claim 2, characterized in that, In the target competitive recovery mode of the supply chain model, based on the initial parameters, the target resource data of the link object is determined using a reverse-order solution algorithm, including: Under the target competitive recycling mode implemented in the supply chain model, the first initial resource data of the recycler is determined based on the transfer price parameter, the first recycling price parameter, and the recycling volume; Based on the initial parameters, the first sales resource parameters and the second sales resource parameters of the retailer are determined, and based on the first sales resource parameters, the second sales resource parameters and the green technology cost, the second initial resource data of the retailer is determined, wherein the first sales resource parameters are the sales resource parameters of the retailer selling new batteries, and the second sales resource parameters are the sales resource parameters of the retailer selling retired batteries. Based on the initial parameters, the manufacturer's first transaction value parameter, second transaction value parameter, and second remanufacturing cost savings of the retired battery are determined. Based on the first transaction value parameter, second transaction value parameter, second remanufacturing cost savings, and green innovation cost, the manufacturer's third initial resource data are determined. The first transaction value parameter is the transaction value parameter for the manufacturer to wholesale the new battery, and the second transaction value parameter is the transaction value parameter for the manufacturer to wholesale the retired battery. Based on the first initial resource data, the second initial resource data, and the third initial resource data, the target resource data is determined using the reverse order solution algorithm.

4. The method according to claim 3, characterized in that, The target resource data includes at least: first target resource data corresponding to the first initial resource data, second target resource data corresponding to the second initial resource data, and third target resource data corresponding to the third initial resource data. The first target resource data includes, according to the following formula: in, Used to represent the first target resource data; Parameters used to indicate the transfer price of the unit of retired battery; Used to represent the recycling price coefficient; Used to represent the intensity coefficient of recycling competition; The second target resource data includes the following formula: in, Used to represent the second target resource data; Used to represent the production cost per unit of new battery; A price sensitivity coefficient used to represent the sales price of recycled batteries; Cost coefficients used to represent the green technology evaluation parameters; Cost coefficient used to represent the parameters of green innovation capability; Used to represent the green technology evaluation sensitivity coefficient of the consumer objects in the link object; The green innovation sensitivity coefficient used to represent the consumer object; The third target resource data includes the following formula: in, Used to represent the third target resource data; Used to indicate the cost savings in remanufacturing per unit of recycled battery; Used to indicate the proportion of retired batteries that can be reused in a tiered manner; This is used to represent the manufacturer's unit resource data when the retired batteries are transferred to the secondary use market.

5. The method according to claim 1, characterized in that, The first cooperative resource data includes at least: first object resource data and second object resource data, wherein the first object resource data is used to represent the resource data of the manufacturer and the retailer constituting a cooperative object, and the second object resource data is used to represent the resource data of the recycler when the supply chain model executes the first cooperative mode; The second cooperative resource data includes at least: third object resource data and fourth object resource data, wherein the third object resource data is used to represent resource data of the cooperative object consisting of the recycler and the manufacturer, and the fourth object resource data is used to represent the resource data of the retailer when the second cooperative mode is implemented in the supply chain model; The third cooperative resource data includes at least: fifth object resource data and sixth object resource data, wherein the fifth object resource data is used to represent the resource data of the cooperative object consisting of the retailer and the recycler, and the sixth object resource data is used to represent the resource data of the manufacturer when the third cooperative mode is implemented in the supply chain model.

6. The method according to claim 5, characterized in that, The first object resource data includes, according to the following formula: in, Used to represent the resource data of the first object; The second object resource data includes the following formula: in, Used to represent the resource data of the second object; The third object resource data includes, according to the following formula: in, Used to represent the resource data of the third object; The fourth object resource data includes the following formula: in, Used to represent the resource data of the fourth object; The fifth object resource data includes the following formula: in, Used to represent the resource data of the fifth object; The sixth object resource data includes the following formula: in, Used to represent the resource data of the sixth object.

7. The method according to claim 1, characterized in that, The fourth cooperative resource data includes, according to the following formula: in, Used to represent the fourth cooperative resource data.

8. A resource allocation device for link objects based on a supply chain model, characterized in that, The device includes: The first determining unit is used to obtain a supply chain model in the scenario of remanufacturing retired batteries, and to determine initial parameters based on the supply chain model, wherein the link objects in the supply chain model include at least: manufacturers, retailers and recyclers; The second determining unit is used to determine the target resource data of the link object based on the initial parameters and using a reverse order solving algorithm under the target competitive recovery mode of the supply chain model. The building unit is used to build a first cooperation model, a second cooperation model, a third cooperation model, and a fourth cooperation model based on the supply chain model. In the first cooperation model, the manufacturer and the retailer are the cooperating parties. In the second cooperation model, the recycler and the manufacturer are the cooperating parties. In the third cooperation model, the retailer and the recycler are the cooperating parties. In the fourth cooperation model, the manufacturer, the retailer, and the recycler are the cooperating parties. The third determining unit is used to determine, respectively, the first cooperative resource data of the supply chain model when executing the first cooperative mode, the second cooperative resource data when executing the second cooperative mode, the third cooperative resource data when executing the third cooperative mode, and the fourth cooperative resource data when executing the fourth cooperative mode using the reverse order solving algorithm. The fourth determining unit is used to determine the resource allocation data of the link object based on the target resource data, the first cooperative resource data, the second cooperative resource data, the third cooperative resource data, and the fourth cooperative resource data, using a target allocation algorithm.

9. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

10. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

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