An Optimization Method for Cross-Border Trade Supply Chain Scheduling Based on Ant Colony Algorithm

Abstract

The present invention relates to the technical field of supply chain planning, and specifically relates to an optimization method for cross-border trade supply chain scheduling based on the ant colony algorithm. This method first highlights the situation among all initial fit degrees according to the initial fit degree corresponding to the company nodes, adjusts the initial fit degree, and obtains the adjusted fit degree; according to the adjusted fit degree of adjacent company node combinations, adjusts the initial transaction quality parameters to obtain the adjusted transaction quality parameters of adjacent company node combinations; according to the adjusted transaction quality parameters of adjacent company node combinations in each supply chain, screens out the optimal supply chain from all the supply chains in the supply chain network. The present invention can better screen out the optimal supply chain by deeply analyzing the transportation cost and the fit degree between companies, and ensure the long-term stable income during the product supply process.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain planning, and particularly relates to a cross-border trade supply chain scheduling optimization method based on the ant colony algorithm. Background Art

[0002] As an important part of the global economy, cross-border trade can promote the optimal allocation of resources among countries, thereby improving production efficiency and resource utilization rate. The core of cross-border trade supply chain scheduling optimization is to optimize the supply chain of products to achieve a more efficient and economical global logistics process. Usually, a supply chain network is constructed based on companies corresponding to industrial link categories, and the optimal supply chain in the supply chain network is searched to ensure the benefits of the supply chain process.

[0003] Since the transportation cost in the transaction process of adjacent company combinations is the core factor affecting profits, the traditional ant colony algorithm usually determines the optimal supply chain based on the transportation cost of adjacent company combinations. However, in the process of determining the optimal supply chain by the traditional ant colony algorithm, the degree of fit in the transaction process of adjacent company combinations is not fully considered, resulting in the inaccuracy of the optimal supply chain and making it difficult to guarantee the long-term benefits of the product supply process. Summary of the Invention

[0004] In order to solve the technical problem that it is difficult to guarantee the long-term profit of the product supply process when determining the optimal supply chain in the prior art, the purpose of the present invention is to provide a cross-border trade supply chain scheduling optimization method based on the ant colony algorithm, and the specific technical solutions adopted are as follows:

[0005] A cross-border trade supply chain scheduling optimization method based on the ant colony algorithm, the method includes:

[0006] Obtain all supply chains in the supply chain network; the supply chain includes company nodes corresponding to each industrial link category; obtain the transportation cost and transaction information of adjacent company node combinations in each transaction process of each supply chain;

[0007] According to the transportation cost of the adjacent company node combination in each of the transaction processes, obtain the initial transaction quality parameter of the adjacent company node combination; according to the transaction information of the adjacent company node combination in each transaction process, obtain the initial degree of fit of the adjacent company node combination; adjust the initial degree of fit according to the prominence of the company node corresponding to the initial degree of fit among all the initial degrees of fit to obtain the adjusted degree of fit; according to the adjusted degree of fit of the adjacent company node combination, adjust the initial transaction quality parameter to obtain the adjusted transaction quality parameter of the adjacent company node combination;

[0008] Filter out the optimal supply chains from all the supply chains in the supply chain network according to the adjusted transaction quality parameters of the adjacent company node combinations described in each supply chain.

[0009] Further, the method for obtaining the initial transaction quality parameters includes:

[0010] Obtain the overall transportation index of the adjacent company node combination according to the overall distribution of the transportation costs of all the transaction processes corresponding to the adjacent company node combination;

[0011] Obtain the initial transaction quality parameters of the adjacent company node combination according to the overall transportation index of the adjacent company node combination; the overall transportation index and the transaction quality parameters are negatively correlated.

[0012] Further, the method for obtaining the initial degree of fit includes:

[0013] The transaction information includes: profit, quality score value, and speed score value; take the profit, quality score value, and speed score value as the transaction indicators to be analyzed respectively;

[0014] Obtain the overall transaction indicators corresponding to the transaction indicators to be analyzed of the adjacent company node combination according to the overall distribution of the transaction indicators to be analyzed of all the transaction processes corresponding to the adjacent company node combination;

[0015] Obtain the initial degree of fit of the adjacent company node combination according to the profit, quality score value, and speed score value corresponding to the overall transaction indicators.

[0016] Further, the method for obtaining the overall transaction indicators includes:

[0017] Calculate the mean value of the transaction indicators to be analyzed of all the transaction processes of the adjacent company node combination to obtain the overall transaction indicators corresponding to the transaction indicators to be analyzed of the adjacent company node combination.

[0018] Further, the method for obtaining the initial degree of fit of the adjacent company node combination according to the profit, quality score value, and speed score value corresponding to the overall transaction indicators includes:

[0019] Calculate the mean value of the overall transaction indicators corresponding to the profit, quality score value, and speed score value, and normalize the mean value to obtain the initial degree of fit of the adjacent company node combination.

[0020] Further, the method for obtaining the adjusted degree of fit includes:

[0021] Take the corresponding degree of fit of all initial combinations of adjacent industrial link categories as the first set of combinations of adjacent industrial link categories; in the first set, take the corresponding degree of fit of all initial company nodes as the second set of company nodes;

[0022] According to the prominence of the second set in the first set, obtain the prominence index of the company node in the first set;

[0023] Take the company nodes with a prominence index greater than the preset prominence threshold as the prominent nodes of the combination of adjacent industrial link categories;

[0024] If there are no prominent nodes in the combination of adjacent industrial link categories, directly take the initial degree of fit in the first set as the adjusted degree of fit;

[0025] If there are prominent nodes in the combination of adjacent industrial link categories, adjust the initial degree of fit in the first set according to the prominence index to obtain the adjusted degree of fit.

[0026] Furthermore, the method for obtaining the prominence index includes:

[0027] Calculate the mean of all initial degrees of fit in the first set to obtain the first mean; calculate the mean of all initial degrees of fit in the second set to obtain the second mean, calculate the difference between the first mean and the second mean, and normalize the difference to obtain the prominence index.

[0028] Furthermore, the method for obtaining the adjusted degree of fit when there are prominent nodes in the combination of adjacent industrial link categories and adjusting the initial degree of fit in the first set according to the prominence index includes:

[0029] In the first set, take the corresponding initial degree of fit of the adjacent company node combination containing the prominent node as the degree to be adjusted; directly take the corresponding initial degree of fit of the adjacent company node combination not containing the prominent node as the adjusted degree of fit;

[0030] For the adjacent company node combination containing the prominent node, calculate the product of the degree to be adjusted corresponding to the prominence index and the preset ratio to obtain the reduction ratio; calculate 1 minus the reduction ratio to obtain the ratio parameter; calculate the product of the ratio parameter and the initial degree of fit to obtain the adjusted degree of fit.

[0031] Furthermore, the method for obtaining the adjusted transaction quality parameter includes:

[0032] Calculate the product of the adjusted degree of fit of the adjacent company node combination and the initial transaction quality parameter to obtain the adjusted transaction quality parameter of the adjacent company node combination.

[0033] Further, the method for obtaining the optimal supply chain includes:

[0034] Based on the ant colony algorithm, using the adjusted transaction quality parameter of the combination of adjacent company nodes as heuristic information, the optimal supply chain is screened out from each supply chain in the supply chain network.

[0035] The present invention has the following beneficial effects:

[0036] Considering that transportation cost is the core factor affecting quality during the transaction process, the lower the transportation cost, the higher the transaction quality. First, based on the transportation cost of the combination of adjacent company nodes in each transaction process, the initial transaction quality parameter of the combination of adjacent company nodes is obtained, and the initial transaction quality parameter is used to preliminarily reflect the transaction quality. Measuring the transaction quality of the combination of adjacent company nodes in the supply chain only by transportation cost is too one-sided. The transaction between companies also needs to be based on the premise of mutual fit between the companies. The initial fit degree is used to preliminarily reflect the fit degree between the combinations of adjacent company nodes. In order to appropriately adjust the initial transaction quality parameter subsequently, the initial fit degree is adjusted to obtain the adjusted fit degree corresponding to the company nodes. Thus, the initial transaction quality parameter is adjusted to obtain the adjusted transaction quality parameter of the combination of adjacent company nodes. The adjusted transaction quality parameter combines the transportation cost and the fit degree between companies, and can more comprehensively reflect the transaction quality. Thus, using the adjusted transaction quality parameter, the optimal supply chain is screened out from all the supply chains in the supply chain network. The optimal supply chain ensures low cost and high profit while also ensuring the mutual fit between companies, and realizes long-term stable benefits in the product supply process. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 It is a flowchart of a cross-border trade supply chain scheduling optimization method based on the ant colony algorithm provided by an embodiment of the present invention;

[0039] Figure 2 It is a schematic diagram of a supply chain network provided by an embodiment of the present invention;

[0040] Figure 3 It is a flowchart of a method for obtaining the initial fit degree provided by an embodiment of the present invention;

[0041] Figure 4Flowchart of a method for obtaining an adjusted degree of fit provided by an embodiment of the present invention. Detailed implementation manners

[0042] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following combines the accompanying drawings and preferred embodiments to detail the specific implementation manners, structures, features and effects of a cross-border trade supply chain scheduling optimization method based on the ant colony algorithm proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0044] The following specifically describes the specific solution of a cross-border trade supply chain scheduling optimization method provided by the present invention with reference to the accompanying drawings.

[0045] An embodiment of the present invention provides a cross-border trade supply chain scheduling optimization method based on the ant colony algorithm. Please refer to Figure 1 , which shows a flowchart of a cross-border trade supply chain scheduling optimization method provided by an embodiment of the present invention. The method includes the following steps:

[0046] Step S1: Obtain all supply chains in the supply chain network; the supply chain includes company nodes corresponding to each industrial link category; obtain the transportation costs and transaction information of adjacent company node combinations in each supply chain during each transaction process.

[0047] In order to determine the optimal supply chain, it is first necessary to obtain all supply chains in the supply chain network and the transportation costs and transaction information of adjacent company node combinations in each supply chain during each transaction process.

[0048] In order to optimize the supply process, considering that the complete supply process of products is from raw material supply to product processing and then to sales, the supply process covers four core industrial links: raw material supply, product manufacturing, product distribution and product retail. Each industrial link corresponds to multiple companies. Each industrial link corresponds to multiple companies, that is, the raw material supply industrial link corresponds to multiple raw material supply companies, the product manufacturing industrial link corresponds to multiple product manufacturing companies, the product distribution industrial link corresponds to multiple product distribution companies, and the product retail industrial link corresponds to multiple product retail companies.

[0049] Take each industrial link as each industrial link category, and the company corresponding to the industrial link as each company node. Connect four company nodes, namely, a company node in the raw material supply category, a company node in the product manufacturing category, a company node in the product distribution category, and a company node in the product retail category, to form a complete supply chain. That is to say, it represents that the supply process is that the raw material supply company sells raw materials to the product manufacturing company, then the product manufacturing company sells the products to the product distribution company, and finally the product distribution company sells the products to the product retail company.

[0050] As an example, Figure 2 shows a schematic diagram of a supply chain network, accurately reflecting the relationships between different company nodes; the raw material supply category includes two company nodes, A1 and A2, which are responsible for providing raw materials; the product manufacturing category includes three company nodes, B1, B2, and B3, which are responsible for processing raw materials into products; the product distribution category has two company nodes, C1 and C2, which are responsible for selling products to each retail point; the product retail category includes four company nodes, D1, D2, D3, and D4, which directly sell products to consumers. Each supply chain includes a company node in the raw material supply category, a company node in the product manufacturing category, a company node in the product distribution category, and a company node in the product retail category. Taking A1-B1-C1-D1 as an example, this is a typical supply chain; taking all the supply chains composed of all company nodes as the supply chain network, the constructed supply chain network can be as Figure 2 shown.

[0051] Among them, in the order of the supply chain, each industrial link category and its previous industrial link category are taken as an adjacent industrial link category combination. The adjacent company node combination refers to the pair of directly connected company nodes corresponding to the adjacent industrial link category combination. For example, the adjacent industrial link category combination is the raw material supply category - the product manufacturing category, and all its corresponding adjacent company node combinations are A1-B1, A1-B2, A1-B3, A2-B1, A2-B2, and A2-B3, indicating that different raw material supply companies provide raw materials to different product manufacturing companies.

[0052] Obtain the transportation costs and transaction information of the companies corresponding to the adjacent company node combinations in each supply chain from the supply chain database. For example, for the transportation costs and transaction information of any transaction process of the adjacent company node combination A1 - B1, the specific obtaining process includes: in any transaction process, calculate the total amount of the transportation process in which the raw material supply company corresponding to A1 provides raw materials to the product manufacturing company corresponding to B1, and use it as the transportation cost of the adjacent company node combination A1 - B1 in this transaction process. The higher the transportation cost, the higher the transaction cost and the less satisfied with this transaction. Take the profit obtained by the raw material supply company corresponding to A1 when providing raw materials to the product manufacturing company corresponding to B1 as the profit of the adjacent company node combination A1 - B1. The higher the profit, the more satisfied with this transaction. The product manufacturing company corresponding to B1 will score the quality of the raw materials provided by the raw material supply company corresponding to A1 to obtain a quality score value. The higher the quality score value, the better the quality and the more satisfied with this transaction. The product manufacturing company corresponding to B1 will score the speed of the raw material supply company corresponding to A1 when providing raw materials to obtain a speed score value. The higher the speed score value, the more timely the delivery and the more satisfied with this transaction. Take the profit, quality score value, and speed score value as the transaction information of the adjacent company node combination A1 - B1 in this transaction process.

[0053] It should be noted that for the convenience of calculation, all the index data involved in the operations in the embodiments of the present invention have undergone data preprocessing, thereby canceling the influence of dimensions. The specific means of canceling the dimension influence are well-known technical means to those skilled in the art and will not be limited here.

[0054] Step S2: Obtain the initial transaction quality parameters of the adjacent company node combination according to the transportation costs of the adjacent company node combination in each transaction process; obtain the initial fit degree of the adjacent company node combination according to the transaction information of the adjacent company node combination in each transaction process; adjust the initial fit degree according to the prominent situation of the initial fit degree corresponding to the company node among all the initial fit degrees to obtain the adjusted fit degree; adjust the initial transaction quality parameters according to the adjusted fit degree of the adjacent company node combination to obtain the adjusted transaction quality parameters of the adjacent company node combination.

[0055] Considering that transportation cost is a core factor affecting the quality during the transaction process, the lower the transportation cost, the higher the transaction quality. First, by the transportation cost of adjacent company node combinations in each transaction process, the initial transaction quality parameters of adjacent company node combinations are obtained, and the transaction quality is initially reflected by the initial transaction quality parameters. Using only transportation cost to measure the transaction quality of adjacent company node combinations in the supply chain is too one-sided. The transaction between companies also needs to be based on the premise of mutual fit between the companies, and the initial degree of fit is used to initially reflect the degree of fit between adjacent company node combinations. In order to make appropriate adjustments to the initial transaction quality parameters subsequently, the initial degree of fit is adjusted to obtain the adjusted degree of fit corresponding to the company nodes. Thus, the initial transaction quality parameters are adjusted to obtain the adjusted transaction quality parameters of adjacent company node combinations. The adjusted transaction quality parameters incorporate both the transportation cost and the degree of fit between companies, and can more comprehensively reflect the transaction quality.

[0056] Considering that cross-border trade involves cross-border logistics, including various transportation modes such as sea transportation, air transportation, and land transportation, as well as possible transshipment, customs clearance and other links, all of which are accompanied by substantial transportation costs, the transportation cost during the transaction process is a core factor affecting profits, and the reciprocal of the transportation cost can initially reflect the transaction quality. The traditional ant colony algorithm uses the reciprocal of the distance between two points as heuristic information. In the embodiments of the present invention, the transportation cost is used to reflect the distance between two company nodes in adjacent company node combinations in the traditional ant colony algorithm. Therefore, it can also be understood correspondingly that when using the traditional ant colony algorithm to determine the supply chain with the optimal transaction quality, usually the reciprocal of the transportation cost of adjacent company node combinations is used as the heuristic information in the ant colony algorithm. The traditional ant colony algorithm often uses the reciprocal of the transportation cost of adjacent company node combinations as heuristic information. Using only transportation cost to measure the transaction quality of adjacent company node combinations in the supply chain is too one-sided. In order to better screen out the optimal supply chain, the present invention constructs adjusted transaction quality parameters to more comprehensively reflect the transaction quality, and thus uses the adjusted transaction quality parameters as heuristic information, enabling the ant colony algorithm to more accurately identify high-quality supply chains during the search process, and thus screening out the optimal supply chain.

[0057] Since transportation cost is a core factor affecting the quality during the transaction process, first, by the transportation cost of adjacent company node combinations in each transaction process, the initial transaction quality parameters of adjacent company node combinations are obtained, and the transaction quality is initially reflected by the initial transaction quality parameters. Preferably, in one embodiment of the present invention, the method for obtaining the initial transaction quality parameters includes:

[0058] Obtain the overall transportation index of the adjacent company node combination according to the overall distribution of the transportation costs corresponding to all transaction processes of the adjacent company node combination; obtain the initial transaction quality parameter of the adjacent company node combination according to the overall transportation index of the adjacent company node combination; the overall transportation index and the transaction quality parameter are negatively correlated.

[0059] Specifically for the above steps, reflect the overall distribution through the mean value, calculate the mean value of the transportation costs of the adjacent company node combination in all transaction processes, and obtain the overall transportation index of the adjacent company node combination; take the reciprocal of the overall transportation index as the initial transaction quality parameter of the adjacent company node combination.

[0060] The overall transportation index can reflect the overall transportation cost of the adjacent company node combination in all transaction processes. The smaller the overall transportation index, the higher the transaction quality of the adjacent company node combination. Furthermore, initially reflect the transaction quality through the initial transaction quality parameter. The larger the initial transaction quality parameter, the higher the transaction quality of the adjacent company node combination.

[0061] Using only transportation costs to measure the transaction quality of adjacent company node combinations in the supply chain is too one-sided. To analyze the degree of fit between adjacent company node combinations, please refer to Figure 3 , which shows a flowchart of a method for obtaining an initial degree of fit in an embodiment of the present invention. Preferably, in an embodiment of the present invention, the method for obtaining the initial degree of fit includes:

[0062] Step S201: The transaction information includes: profit, quality score value, and speed score value; use the profit, quality score value, and speed score value as the transaction indicators to be analyzed respectively.

[0063] To measure the degree of fit of adjacent company node combinations, considering that the higher the profit, quality score value, and speed score value in each transaction process, the more satisfied the company is with the transaction, and the more fitting the adjacent company node combination is in the transaction process, use the profit, quality score value, and speed score value as the transaction indicators to be analyzed respectively.

[0064] Step S202: Obtain the overall transaction indicator corresponding to the transaction indicator to be analyzed of the adjacent company node combination according to the overall distribution of the transaction indicators to be analyzed corresponding to all transaction processes of the adjacent company node combination.

[0065] The overall transaction indicator reflects the overall performance of the transaction indicators to be analyzed of all transaction processes of the adjacent company node combination.

[0066] Preferably, in an embodiment of the present invention, calculate the mean value of the transaction indicators to be analyzed of all transaction processes of the adjacent company node combination to obtain the overall transaction indicator corresponding to the transaction indicator to be analyzed of the adjacent company node combination.

[0067] Step S203: Obtain the initial degree of fit of the adjacent company node combination corresponding to the overall transaction indicators according to the profit, quality score value, and speed score value.

[0068] The greater the initial degree of fit, it indicates that the adjacent company node combination has better profit, product quality, and delivery speed during the transaction, is more satisfied with both parties to the transaction, and the degree of fit between the adjacent company node combinations is higher.

[0069] Preferably, in an embodiment of the present invention, calculate the mean value of the overall transaction indicators corresponding to the profit, quality score value, and speed score value, and normalize the mean value to obtain the initial degree of fit of the adjacent company node combination. In an embodiment of the present invention, the normalization method adopted is: perform normalization using the sigmoid normalization function.

[0070] Considering that analyzing the degree of fit of the adjacent company node combination is used to adjust the initial transaction quality parameters, obtain the adjusted transaction quality parameters of the adjacent company node combination, and thus use the adjusted transaction quality parameters as heuristic information. Its size directly affects the preference when selecting paths in the ant colony algorithm process. If the adjusted transaction quality parameters are too large, the algorithm may fall into a local optimal solution and cannot find the global optimal solution. In order to reduce the possibility of generating local optimality, appropriately weaken the original data used to calculate the adjusted transaction quality parameters, that is, when the initial degree of fit is too large, so as to reduce the local optimal risk caused by the too large adjusted transaction quality parameters. This can enable the ant colony algorithm to more evenly consider various factors during the search process and improve the ability to identify high-quality supply chains.

[0071] For example, for the adjacent industrial link category combination of raw material supply category - product manufacturing category, if the initial degree of fit between company node A1 in the raw material supply category and its adjacent company nodes B1, B2, B3 is too large, while the initial degree of fit between other company nodes in the raw material supply category and their adjacent company nodes is relatively small, and the importance of company node A1 is significantly higher than other company nodes in the industrial link category, the ant colony algorithm may overly rely on this high-importance node during the search process and tend to select the paths connected to company node A1, even if these paths are not optimal globally. In order to reduce the risk of generating local optimality, it is necessary to appropriately adjust the initial degree of fit to obtain the adjusted degree of fit corresponding to the company node. Please refer to Figure 4 , which shows a flowchart of a method for obtaining an adjusted degree of fit in an embodiment of the present invention. Preferably, in an embodiment of the present invention, the method for obtaining the adjusted degree of fit includes:

[0072] Step S211: Take all the initial fit degrees corresponding to the adjacent industrial link category combinations as the first set of the adjacent industrial link category combinations; in the first set, take all the initial fit degrees corresponding to the company nodes as the second set of the company nodes.

[0073] Constructing the first set and the second set provides data support for highlighting indicators in subsequent analysis.

[0074] For example, for the adjacent industrial link category combination of raw material supply category - product manufacturing category, all the initial fit degrees corresponding to the raw material supply category - product manufacturing category are the initial fit degrees of all adjacent company node combinations. That is, the first set of the adjacent industrial link category combinations includes the initial fit degrees of A1 - B1, A1 - B2, A1 - B3, A2 - B1, A2 - B2, and A2 - B3. In the first set, take all the initial fit degrees corresponding to the company node A1 as the second set of the company nodes, that is, the second set includes the initial fit degrees of A1 - B1, A1 - B2, and A1 - B3.

[0075] Step S212: Obtain the highlighting indicator of the company node in the first set according to the highlighting situation of the second set in the first set;

[0076] The highlighting indicator reflects the highlighting situation of the initial fit degree corresponding to the company node among all the initial fit degrees of the adjacent industrial link categories to which it belongs. The larger the highlighting indicator, the greater the highlighting degree, the greater the possibility that the company node is a high - importance company node, and the easier it is to generate a local optimum.

[0077] Preferably, in an embodiment of the present invention, the method for obtaining the highlighting indicator includes:

[0078] Calculate the mean value of all the initial fit degrees in the first set to obtain the first mean value; calculate the mean value of all the initial fit degrees in the second set to obtain the second mean value, calculate the difference between the first mean value and the second mean value, and normalize the difference to obtain the highlighting indicator. In an embodiment of the present invention, the method for normalization is: use the norm normalization function for normalization, and limit the numerical range between 0 and 1.

[0079] Step S213: Take the company nodes with highlighting indicators greater than the preset highlighting threshold as the highlighting nodes of the adjacent industrial link category combinations.

[0080] The highlighting nodes of the adjacent industrial link category combinations represent high - importance company nodes in the adjacent industrial link category combinations, which are likely to cause the ant colony algorithm to fall into a local optimum.

[0081] In one embodiment of the present invention, 0.21 is used as a preset prominence threshold, which is used to screen prominent nodes. If the implementer wants to screen out more prominent nodes, the preset prominence threshold can be appropriately reduced according to the implementation scenario by the implementer, and no limitation is made here.

[0082] Step S214: If there are no prominent nodes in the adjacent industrial link category combination, directly use the initial fit degree in the first set as the adjusted fit degree.

[0083] Considering that there are no prominent nodes in the adjacent industrial link category combination, it means that there are no company nodes of high importance, and there is no need to adjust the initial fit degree in the first set. Directly use the initial fit degree in the first set as the adjusted fit degree.

[0084] Step S215: If there are prominent nodes in the adjacent industrial link category combination, adjust the initial fit degree in the first set according to the prominence index to obtain the adjusted fit degree.

[0085] Considering that there are prominent nodes in the adjacent industrial link category combination, it is necessary to appropriately reduce the initial fit degree corresponding to the prominent nodes to reduce the risk of generating local optima.

[0086] Preferably, in one embodiment of the present invention, in the first set, the initial fit degree corresponding to the adjacent company node combination containing prominent nodes is used as the degree to be adjusted; the initial fit degree corresponding to the adjacent company node combination not containing prominent nodes is directly used as the adjusted fit degree;

[0087] For the adjacent company node combination containing prominent nodes, calculate the product of the degree to be adjusted corresponding to the prominence index and the preset ratio to obtain the reduction ratio; calculate 1 minus the reduction ratio to obtain the ratio parameter; calculate the product of the ratio parameter and the initial fit degree to obtain the adjusted fit degree. In one embodiment of the present invention, the preset ratio is 10%, and the implementer can set it according to the implementation scenario. It should be noted that for the degree to be adjusted corresponding to the prominence index, if there is one prominent node in the adjacent company node combination to which the degree to be adjusted belongs, it is the prominence index of the prominent node in the adjacent company node combination to which the degree to be adjusted belongs. If there are two prominent nodes in the adjacent company node combination to which the degree to be adjusted belongs, that is, the adjustment degree corresponds to two prominence indexes, and the average value of the two prominence indexes is used as the prominence index corresponding to the degree to be adjusted.

[0088] For the above steps, in the first set, the initial degree of fit corresponding to the combination of adjacent company nodes containing prominent nodes is used as the degree to be adjusted; the degree to be adjusted reflects the initial degree of fit corresponding to the prominent nodes. Considering that in order to reduce the risk of generating local optima, it is necessary to reduce the initial degree of fit corresponding to the prominent nodes. For the initial degree of fit corresponding to non-prominent nodes, no adjustment is required. The initial degree of fit corresponding to the combination of adjacent company nodes that do not contain prominent nodes is directly used as the adjusted degree of fit. For the degree to be adjusted, the degree of reduction in the initial degree of fit corresponding to the prominent nodes determined according to the prominence situation is reflected by a reduction ratio. Through the above steps, the adjusted degree of fit can effectively reduce the local optimum risk caused by prominent nodes and can better adjust the initial transaction quality parameters.

[0089] By constructing the adjusted transaction quality parameters, the transaction quality can be more comprehensively reflected, so that the adjusted transaction quality parameters can be used as heuristic information for subsequent use, enabling the ant colony algorithm to more accurately identify high-quality supply chains during the search process.

[0090] Preferably, in an embodiment of the present invention, the method for obtaining the adjusted trade quality includes:

[0091] Calculate the product of the adjusted degree of fit of the adjacent company node combination and the initial transaction quality parameter to obtain the adjusted transaction quality parameter of the adjacent company node combination. The adjusted transaction quality parameter combines the transportation cost and the degree of fit between companies, can more comprehensively reflect the transaction quality, and can also effectively avoid local optima.

[0092] Step S3: According to the adjusted transaction quality parameters of the adjacent company node combinations in each supply chain, screen out the optimal supply chain from all the supply chains in the supply chain network.

[0093] Considering that the adjusted transaction quality parameters can more comprehensively reflect the transaction quality, the adjusted transaction quality parameters are used to screen out the optimal supply chain from all the supply chains in the supply chain network. The optimal supply chain ensures low cost and high profit while also ensuring the mutual fit between companies, realizing long-term stable benefits in the product supply process.

[0094] Preferably, in an embodiment of the present invention, the method for obtaining the optimal supply chain includes:

[0095] Based on the ant colony algorithm, the adjusted transaction quality parameters of the adjacent company node combinations are used as heuristic information to screen out the optimal supply chain from each supply chain in the supply chain network.

[0096] Using the adjusted transaction quality parameter as heuristic information enables the ant colony algorithm to more accurately identify high-quality supply chains during the search process, thereby screening out the optimal supply chain. The optimal supply chain can better ensure the long-term stable benefits in the product supply process.

[0097] It should be noted that the ant colony algorithm is a well-known technical means in the art. Here, only the steps of screening out the optimal supply chain from each supply chain in the supply chain network by using the adjusted transaction quality parameter of the combined adjacent company nodes as heuristic information are briefly described:

[0098] First, set the parameters of the ant colony algorithm and use the adjusted transaction quality parameter of the combined adjacent company nodes as heuristic information. In the supply chain network, each ant starts from the starting company node, calculates the transfer probability based on the pheromone concentration and heuristic information at the current position, selects the next company node as the target point, and returns to the starting company node corresponding to the supply chain after visiting a supply chain. Update the pheromone matrix according to the length of the supply chain passed by the ant and the pheromone update rule. Pheromone update usually includes two processes: pheromone evaporation and pheromone enhancement. Repeat the steps of ant movement and pheromone update until the termination condition is met, and finally output the found optimal supply chain.

[0099] Specifically, apply the optimal supply chain to the supply process to achieve the long-term stable benefits in the product supply process.

[0100] In summary, the embodiment of the present invention provides a cross-border trade supply chain scheduling optimization method based on the ant colony algorithm. First, obtain the initial transaction quality parameter of the combined adjacent company nodes through the transportation cost in each transaction process of the combined adjacent company nodes; adjust the initial fit degree according to the prominent situation of the initial fit degree corresponding to the company nodes among all the initial fit degrees to obtain the adjusted fit degree; adjust the initial transaction quality parameter according to the adjusted fit degree of the combined adjacent company nodes to obtain the adjusted transaction quality parameter of the combined adjacent company nodes; screen out the optimal supply chain from all the supply chains in the supply chain network according to the adjusted transaction quality parameter of the combined adjacent company nodes in each supply chain. In the embodiment of the present invention, by deeply exploring the transportation cost and the fit degree between companies, the optimal supply chain is better screened out to ensure the long-term stable benefits in the product supply process.

[0101] It should be noted that the above sequence of the embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A cross-border trade supply chain scheduling optimization method based on ant colony algorithm, characterized in that: The method comprises: Obtain all supply chains in the supply chain network; the supply chain includes company nodes corresponding to each industry link category; obtain the transportation cost and transaction information of the combination of adjacent company nodes in each supply chain in each transaction process; According to the transportation cost of the adjacent company node combination in each transaction process, the initial transaction quality parameters of the adjacent company node combination are obtained; according to the transaction information of the adjacent company node combination in each transaction process, the initial degree of fit of the adjacent company node combination is obtained; according to the prominence of the initial degree of fit of the company node corresponding to all initial degrees of fit in, the initial degree of fit is adjusted to obtain the adjusted degree of fit; according to the adjusted degree of fit of the adjacent company node combination, the initial transaction quality parameters are adjusted to obtain the adjusted transaction quality parameters of the adjacent company node combination; According to the adjusted transaction quality parameters of the adjacent company node combination in each supply chain, the optimal supply chain is selected from all supply chains in the supply chain network; The method for obtaining the adjusted degree of fit includes: The corresponding adjacent industry link category combinations to all initial fit degrees are used as a first set of adjacent industry link category combinations; in the first set, the corresponding company nodes to all initial fit degrees are used as a second set of company nodes; According to the prominence of the second set in the first set, obtaining the prominence index of the company node in the first set; The company nodes whose prominence index is greater than the preset prominence threshold are regarded as the prominence nodes of the adjacent industrial link category combination; If there is no prominent node in the combination of adjacent industrial link categories, the initial degree of fit in the first set is directly used as the adjusted degree of fit; If there are prominent nodes in the combination of adjacent industrial links, the initial degree of fit in the first set is adjusted according to the prominent index to obtain the adjusted degree of fit; The method for obtaining the outstanding indicator includes: The mean of all initial fit degrees in the first set is calculated to obtain a first mean; the mean of all initial fit degrees in the second set is calculated to obtain a second mean, the first mean is subtracted from the second mean to obtain a difference, the difference is normalized to obtain a prominent index.

2. According to the cross-border trade supply chain scheduling optimization method based on ant colony algorithm according to claim 1, it is characterized in that: The method for obtaining the initial transaction quality parameter includes: According to the overall distribution of the transportation costs of the adjacent company node combination corresponding to all the transaction processes, the overall transportation index of the adjacent company node combination is obtained; According to the overall transport index of the adjacent company node combination, the initial transaction quality parameter of the adjacent company node combination is obtained; the overall transport index and the transaction quality parameter are negatively correlated.

3. According to the cross-border trade supply chain scheduling optimization method based on ant colony algorithm in claim 1, it is characterized in that: The method for obtaining the initial degree of fit includes: The transaction information includes: profit, quality score value and speed score value; the profit, quality score value and speed score value are respectively used as transaction indicators to be analyzed; According to the overall distribution of the transaction indicators to be analyzed corresponding to all transaction processes of the adjacent company node combination, the transaction indicators to be analyzed corresponding to the overall transaction indicators of the adjacent company node combination are obtained; According to the profit, quality score and speed score corresponding to the overall transaction index, the initial degree of fit of the adjacent company node combination is obtained.

4. According to claim 3, a cross-border trade supply chain scheduling optimization method based on ant colony algorithm is characterized in that: The method for obtaining the overall transaction index includes: The mean of the transaction indicators to be analyzed of all transaction processes of the adjacent company node combination is calculated to obtain the overall transaction indicator corresponding to the transaction indicators to be analyzed of the adjacent company node combination.

5. According to claim 3, a cross-border trade supply chain scheduling optimization method based on ant colony algorithm is characterized in that: The method for obtaining the initial degree of fit of the adjacent company node combination according to the profit, quality score value and speed score value corresponding to the overall transaction indicator includes: Calculate the mean of the overall transaction indicators corresponding to the profit, quality score and speed score, normalize the mean, and obtain the initial degree of fit of the adjacent company node combination.

6. According to claim 5, a cross-border trade supply chain scheduling optimization method based on ant colony algorithm is characterized in that: If there is a prominent node in the combination of adjacent industrial links, the initial degree of fit in the first set is adjusted according to the prominent index, and the method for obtaining the adjusted degree of fit includes: In the first set, the initial fit degree corresponding to the combination of adjacent company nodes containing the prominent node is used as the degree to be adjusted; the initial fit degree corresponding to the combination of adjacent company nodes not containing the prominent node is directly used as the adjusted fit degree; For the combination of adjacent company nodes including the prominent node, the product of the prominent index corresponding to the degree to be adjusted and the preset ratio is calculated to obtain the reduction ratio; 1 minus the reduction ratio is calculated to obtain the ratio parameter; the ratio parameter is calculated and multiplied by the initial degree of fit to obtain the adjusted degree of fit.

7. The cross-border trade supply chain scheduling optimization method based on ant colony algorithm according to claim 1 is characterized in that: The method for obtaining the adjusted transaction quality parameter includes: The product of the adjusted degree of fit of the adjacent company node combination and the initial transaction quality parameter is calculated to obtain the adjusted transaction quality parameter of the adjacent company node combination.

8. According to the cross-border trade supply chain scheduling optimization method based on ant colony algorithm in claim 1, it is characterized in that: The method for obtaining the optimal supply chain includes: Based on the ant colony algorithm, the adjusted transaction quality parameters of the combination of adjacent company nodes are used as heuristic information to screen out the optimal supply chain from each supply chain in the supply chain network.

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