A supply chain management method, system, device, and medium

Abstract

The application relates to the technical field of supply chain management, and in particular to a supply chain management method, system, device and medium. The method comprises the following steps: receiving order demand information uploaded by a client, selecting multiple candidate combinations capable of meeting the order demand information from supply chain participants, each candidate combination comprising a supplier, a manufacturer and a warehousing party; determining a comprehensive score of each candidate combination, determining a candidate combination with the highest comprehensive score as an optimal combination; obtaining to-be-warehoused orders of the warehousing party in the optimal combination, generating a to-be-warehoused order list according to the order demand information of each to-be-warehoused order; determining a carrier of each to-be-warehoused order in the to-be-warehoused order list, and sending a transportation request of each to-be-warehoused order to the corresponding carrier to guide the execution of a transportation task. The application can realize integrated scheduling of supply chain full-link subject selection and order fulfillment, and improve overall collaborative efficiency and rationality of resource allocation.

Description

Technical Field

[0001] This application relates to the field of supply chain management technology, and in particular to a supply chain management method, system, device and medium. Background Technology

[0002] In the current supply chain management field, with the rapid growth of e-commerce and multi-category order demand, the number of supply chain participants is increasing and the coordination links are becoming more complex. Most existing technologies adopt a segmented management model for suppliers, manufacturers, warehouses and logistics providers, which only conducts independent scheduling and selection for a single link. They fail to coordinate and optimize the supply chain as a whole, making it difficult to select the optimal combination of supply chain execution entities from a full-link perspective. At the same time, there is a lack of integrated collaborative scheduling in the order outbound sorting and carrier allocation links. Summary of the Invention

[0003] To address the technical problems of low resource allocation efficiency and difficulty in achieving an optimal balance between overall cost and performance in the entire supply chain, this application provides a supply chain management method, system, equipment, and medium.

[0004] Firstly, this application provides a supply chain management method, which adopts the following technical solution: A supply chain management method, comprising: The system receives order demand information uploaded by the client and selects multiple candidate combinations from supply chain participants that can meet the order demand information. Each candidate combination includes a supplier, a manufacturer, and a warehouse provider. Determine the comprehensive score for each candidate combination, and determine the candidate combination with the highest comprehensive score as the best combination; Obtain the outbound orders from the warehouse in the optimal combination, and generate an outbound order list based on the order demand information of each outbound order; The carrier for each order in the list of orders to be shipped is determined, and the transportation request for each order is sent to the corresponding carrier to guide the execution of the transportation task.

[0005] By adopting the above technical solution, order requirements are received and multiple candidate combinations including suppliers, manufacturers, and warehouse providers are selected. The best combination is then determined by a comprehensive score. Subsequently, a list of orders to be shipped is generated based on the warehouse providers of the best combination, and carriers are matched and transportation instructions are issued. This achieves integrated selection of all entities in the supply chain and integrated scheduling of order fulfillment, thereby improving overall collaborative efficiency and the rationality of resource allocation.

[0006] In a preferred embodiment, this application can be further configured such that determining the comprehensive score for each candidate combination includes: Determine the overall cost, performance reliability, and delivery time of the target candidate combination, wherein the target candidate combination is any one of the plurality of candidate combinations; The maximum and minimum comprehensive costs are determined from the comprehensive costs of the multiple candidate combinations, and the maximum and minimum delivery times are determined from the delivery times of the multiple candidate combinations. The pre-built comprehensive score calculation model is invoked, and the maximum comprehensive cost, the minimum comprehensive cost, the maximum delivery time, the minimum delivery time, and the comprehensive cost, performance reliability, and delivery time of the target candidate combination are substituted into the comprehensive score calculation model to obtain the comprehensive score of the target candidate combination.

[0007] By adopting the above technical solutions, the comprehensive cost, performance reliability and delivery time of candidate combinations are determined respectively, and the extreme values ​​of cost and delivery time are extracted and substituted into the preset model to calculate the comprehensive score. This achieves normalized and quantitative comparison of multi-dimensional indicators, making the evaluation of the combination's merits more objective and unified, and ensuring that the selection of the best combination is accurate and reliable.

[0008] In a preferred embodiment, this application can be further configured to: determine the comprehensive cost of the target candidate combination, including: Determine the material costs of suppliers, the production costs of manufacturers, and the warehousing costs of warehouse providers in the target candidate combinations; Determine the first transportation cost between the supplier and the manufacturer and the second transportation cost between the manufacturer and the warehouse in the target candidate combination, and calculate the sum of the first transportation cost and the second transportation cost to obtain the transportation cost; The sum of the material cost, the production cost, the warehousing cost, and the transportation cost is calculated to obtain the comprehensive cost of the target candidate combination.

[0009] By adopting the above technical solution, the comprehensive cost is broken down into the costs of materials, production, warehousing, and two stages of transportation, and each item is added up and calculated. This comprehensively covers the cost composition of the entire upstream process of the supply chain, avoids cost omissions, provides real and complete cost data support for comprehensive scoring, and improves the economic efficiency of decision-making.

[0010] In a preferred embodiment, this application may be further configured such that, prior to determining the candidate combination with the highest comprehensive score as the optimal combination, the method further includes: For each candidate combination, a supply chain risk cost accounting factor is introduced, and the risk cost includes material shortage risk cost, production delay risk cost and inventory backlog risk cost. Based on historical risk data, the expected value of each risk cost is calculated using the Monte Carlo simulation method; The overall score of the candidate combination is updated using the expected value.

[0011] By adopting the above technical solutions, multiple risk cost accounting factors are introduced before determining the optimal combination. Monte Carlo simulation is used to calculate the expected value of risk and update the comprehensive score. Potential risks are quantified and integrated into the evaluation system, which effectively reduces the probability of high-risk combinations being selected and improves the overall stability and risk resistance of the supply chain.

[0012] In a preferred example, this application can be further configured to: generate a list of orders to be shipped based on the order demand information of each order to be shipped, including: Extract the required delivery time and order priority from the order demand information of each order awaiting shipment; The order list to be shipped is generated by sorting the orders according to a multi-level rule based on the order priority as the first sorting criterion and the required delivery time as the second sorting criterion.

[0013] By adopting the above technical solution, a multi-level rule sorting is performed based on order priority as the primary criterion and required delivery time as the secondary criterion, which quickly generates a list of orders to be shipped out. This ensures that urgent orders are shipped out first, meets timeliness requirements, simplifies the sorting logic, and balances fulfillment efficiency and customer experience.

[0014] In a preferred embodiment, this application can be further configured such that determining the carrier for each order in the list of orders to be shipped includes: Simultaneously send transportation demand information to multiple candidate carriers corresponding to each order in the order list to be shipped out, the transportation demand information including cargo attributes, planned loading time, delivery time window and planned transportation route; For each order to be shipped, receive quotation information from each candidate carrier, including transportation cost quotes, planned transportation time, and available transportation capacity; Based on the quoted information, the matching degree between each candidate carrier and the corresponding order to be shipped is calculated; For each order awaiting shipment, select the candidate carrier with the highest matching degree as the carrier.

[0015] By adopting the above technical solution, transportation needs are sent to multiple candidate carriers simultaneously, quotations are collected and the matching degree is calculated, and the best carrier is selected. This achieves fair bidding and intelligent matching of transportation resources, and improves capacity adaptability and performance timeliness while controlling transportation costs.

[0016] In a preferred embodiment, this application can be further configured such that: the selection of multiple candidate combinations from supply chain participants that can satisfy the order demand information includes: Obtain the capability information of the aforementioned supply chain participants; Based on the capability information and the order demand information, a subset of candidate suppliers, a subset of candidate manufacturers, and a subset of candidate warehousing providers are selected; The elements of the candidate supplier subset, the candidate manufacturer subset, and the candidate warehousing subset are combined to generate multiple candidate combinations.

[0017] By adopting the above technical solution, we first obtain the capability information of each participant and select three qualified candidate subsets, and then combine them to generate candidate solutions. This ensures that all combinations meet the basic requirements of the order, narrows the optimization scope, and improves the efficiency and effectiveness of subsequent comprehensive scoring and selection of the best combination.

[0018] Secondly, this application provides a supply chain management system, which adopts the following technical solution: A supply chain management system, comprising: The receiving module is used to receive order demand information uploaded by the client and select multiple candidate combinations from the supply chain participants that can meet the order demand information. Each candidate combination includes a supplier, a manufacturer, and a warehouse. The first determining module is used to determine the comprehensive score of each candidate combination, and to determine the candidate combination with the highest comprehensive score as the best combination; The generation module is used to obtain the outbound orders of the warehouse in the optimal combination, and generate a list of outbound orders based on the order demand information of each outbound order. The second determining module is used to determine the carrier for each outbound order in the list of outbound orders, and send the transportation request for each outbound order to the corresponding carrier to guide the execution of the transportation task.

[0019] Thirdly, this application provides an electronic device that adopts the following technical solution: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the supply chain management method as described in any of the first aspects.

[0020] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the supply chain management method as described in any of the first aspects.

[0021] Fifthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the supply chain management method as described in any of the first aspects.

[0022] In summary, this application includes the following beneficial technical effects: This application receives order requests and filters out multiple candidate combinations including suppliers, manufacturers, and warehousing providers. The best combination is then determined by a comprehensive score. Subsequently, a list of orders to be shipped is generated based on the best combination of warehousing providers, and carriers are matched and transportation instructions are issued. This enables the integrated selection of entities across the entire supply chain and the unified scheduling of order fulfillment, thereby improving overall collaborative efficiency and the rationality of resource allocation. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating a supply chain management method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a supply chain management system provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] The following is in conjunction with the appendix Figure 1 To be continued Figure 3 This application will be described in further detail.

[0025] This specific embodiment is merely an explanation of this application and is not intended to limit it. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0028] It should be noted that all data interaction processes involved in this application have corresponding transmission protocols, including authorized data collection and use, and both parties involved in the data interaction have completed data authorization through the execution of the protocol.

[0029] This application provides a supply chain management method, such as... Figure 1 As shown, the method provided in this application embodiment is executed by an electronic device, which can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication. This application embodiment does not impose any limitations on this connection. The method includes steps S101-S104, wherein: S101. Receive order demand information uploaded by the client, and select multiple candidate combinations from the supply chain participants that can meet the order demand information. Each candidate combination includes suppliers, manufacturers and warehouse providers.

[0030] The client refers to the operating terminal used by order requesters such as buyers, distributors, and end customers, including PC systems, mobile apps, and mini-programs. Order request information is complete data uploaded by the requester that contains the core fulfillment requirements of the order, including material category, material specifications, material quantity required, delivery time, delivery location, and quality standards.

[0031] Electronic devices receive order request information uploaded by clients through a preset data interface, perform format and integrity checks on the received information, discard invalid orders with missing information or incorrect format, and assign a unique number to valid orders to complete the standardized storage of order request information.

[0032] Supply chain participants refer to entities with corresponding service capabilities throughout the entire supply chain, categorized as suppliers, manufacturers, and warehousing providers. Suppliers provide the raw materials and components needed for production, manufacturers process materials and produce products, and warehousing providers offer storage, sorting, and outbound services. A candidate combination refers to a unit that includes one supplier, one manufacturer, and one warehousing provider, where the capabilities of all three can match the order requirements.

[0033] S102. Determine the comprehensive score of each candidate combination, and determine the candidate combination with the highest comprehensive score as the best combination.

[0034] For each candidate combination, three core indicators—overall cost, fulfillment reliability, and delivery time—are calculated. Overall cost and delivery time are standardized and normalized to eliminate dimensional differences. Using a pre-defined comprehensive score calculation model, the comprehensive score for each candidate combination is calculated by substituting the data for each indicator. All candidate combinations are then sorted in descending order of their comprehensive scores, and the candidate combination with the highest comprehensive score is marked as the optimal supply chain execution combination for this order.

[0035] S103. Obtain the outbound orders from the warehouse in the best combination, and generate a list of outbound orders based on the order demand information of each outbound order.

[0036] Among them, pending outbound orders refer to orders that have been produced and put into storage, and are stored in the warehouse of the warehousing party, waiting for sorting, packaging and outbound operations; the pending outbound order list refers to the order list arranged in the optimized outbound order, which is the basis for the warehousing party to carry out outbound operations.

[0037] Electronic devices interface with the warehouse management system in the optimal combination to automatically obtain complete information on all pending outbound orders under that warehouse. A collaborative optimization model is constructed with the optimization objectives of minimizing average order waiting time and minimizing total transportation cost. The order outbound order is used as the optimal solution, and a genetic algorithm is employed to solve the model. Iterative convergence conditions are set, and when the algorithm iterates to the point where the fitness function converges, the optimal order outbound order is output. All pending outbound orders are then organized according to this optimal order to generate a standardized list of pending outbound orders, which is then distributed to the warehouse's operational terminal.

[0038] S104. Determine the carrier for each pending outbound order in the pending outbound order list, and send the transportation request for each pending outbound order to the corresponding carrier to guide the execution of the transportation task.

[0039] Among them, the carrier refers to a logistics company or transportation team with cargo transportation capabilities and the ability to undertake order delivery tasks; the transportation request refers to the instruction information issued by the system to the carrier, which contains all the transportation requirements and is used to guide the entire process of transportation task execution.

[0040] For each order in the pending outbound order list, multiple candidate carriers with corresponding transportation capabilities are first selected. Transportation demand information is simultaneously sent to all candidate carriers, and price quotes from each carrier are received in real time. Based on the price quotes, a pre-defined matching degree calculation model is used to calculate the matching degree between each candidate carrier and the order. The candidate carrier with the highest matching degree is selected as the final carrier for that order. A standardized transportation request is generated, integrating order information, loading requirements, transportation routes, and delivery requirements, and then sent to the corresponding carrier's scheduling system. The carrier then executes the entire process of loading, transporting, and delivering the goods according to the transportation request.

[0041] This embodiment receives order requests and filters out multiple candidate combinations including suppliers, manufacturers, and warehouse providers. The best combination is then determined by a comprehensive score. Subsequently, a list of orders to be shipped is generated based on the warehouse provider of the best combination, and carriers are matched and transportation instructions are issued. This achieves integrated selection of entities across the entire supply chain and unified scheduling of order fulfillment, thereby improving overall collaborative efficiency and the rationality of resource allocation.

[0042] One possible implementation of this application embodiment involves determining the comprehensive score for each candidate combination, including: Determine the overall cost, performance reliability, and delivery time of the target candidate combination, which is any one of multiple candidate combinations; Determine the maximum and minimum combined costs from the combined costs of multiple candidate combinations, and determine the maximum and minimum delivery times from the delivery times of multiple candidate combinations; The pre-built comprehensive score calculation model is invoked, and the maximum comprehensive cost, minimum comprehensive cost, maximum delivery time, minimum delivery time, as well as the comprehensive cost, performance reliability, and delivery time of the target candidate combination are substituted into the comprehensive score calculation model to obtain the comprehensive score of the target candidate combination.

[0043] In this embodiment, the comprehensive cost includes the supplier's material costs, the manufacturer's production costs, the warehouse provider's warehousing costs, and the transportation costs at each stage. The sum of these costs is calculated as the comprehensive cost.

[0044] For performance reliability, historical performance data for each participant within the target candidate combination is retrieved from the system database, including on-time delivery rate, product quality pass rate, and number of defaults. Evaluation dimensions and weights are set according to actual needs; optionally, on-time delivery rate is weighted at 40%, product quality pass rate at 40%, and historical defaults at 20%. The raw data for each dimension is converted into standardized scores from 0 to 100. For example, on-time delivery rate = (Number of orders delivered on time / Total number of orders delivered) × 100 points; product quality pass rate = (Number of qualified products / Total number of products) × 100 points. The maximum and minimum historical default counts are determined from each candidate combination. The historical default count of the target candidate combination is used as the current historical default count. Historical default count = (Maximum historical default count - Current historical default count) / (Maximum historical default count - Minimum historical default count) × 100 points. The standardized scores for each dimension are multiplied by their corresponding weights and then summed to obtain the quantitative score for the performance reliability of the target candidate combination.

[0045] Delivery time refers to the total time taken from receiving an order request to delivering the final goods to the client for the target candidate combination. It is a core indicator for measuring supply chain fulfillment efficiency, encompassing the total time spent on the entire process, including material procurement, production, warehousing, and transportation. The standard delivery time for each stage is calculated separately: supplier material procurement and transportation time (from supplier to manufacturer), manufacturer production and processing time, and product transportation time from manufacturer to warehousing. The total delivery time is then calculated by summing the time spent on each stage: Delivery Time = Material Procurement and Transportation Time + Production Time + Product Warehousing and Transportation Time. The total standard delivery time for the target candidate combination can be obtained by estimating the time spent on each stage based on the respective capabilities of the participating parties.

[0046] The reliability of contract performance is presented on a 100-point scale, while overall cost and delivery time are not standardized. The overall score calculation model is as follows: Where S is the overall score; C is the overall cost; R is the performance reliability score; T is the delivery time; λ1, λ2, and λ3 are preset weights, and λ1+λ2+λ3=1.

[0047] This embodiment determines the comprehensive cost, performance reliability, and delivery time of candidate combinations, and extracts the extreme values ​​of cost and delivery time into a preset model to calculate the comprehensive score. This achieves normalized and quantitative comparison of multi-dimensional indicators, making the evaluation of the combination's merits more objective and unified, and ensuring that the selection of the best combination is accurate and reliable.

[0048] One possible implementation of this application embodiment is to determine the comprehensive cost of the target candidate combination, including: Determine the material costs of suppliers, the production costs of manufacturers, and the warehousing costs of warehouse providers in the target candidate combination; Determine the first transportation cost between the supplier and the manufacturer and the second transportation cost between the manufacturer and the warehouse in the target candidate combination, and calculate the sum of the first transportation cost and the second transportation cost to obtain the transportation cost; The sum of material costs, production costs, warehousing costs, and transportation costs is calculated to obtain the comprehensive cost of the target candidate combination.

[0049] In this embodiment, for material costs, the material quotations from suppliers in the target candidate combination are retrieved, and the total material purchase price is calculated based on the material requirements of the order. Material cost = material unit price × material requirement. Simultaneously, additional costs such as taxes and transportation losses are checked and included in the material cost statistics. For production costs, the manufacturer's production process parameters and unit product production cost data are obtained, and the total production input is calculated based on the product production quantity required by the order. The formula is: Production cost = unit product production cost × product production quantity.

[0050] For warehousing costs, the warehousing billing standard of the warehousing provider is used: Warehousing cost = Unit volume / Duration warehousing fee × Storage volume × Warehousing duration. Warehousing duration is estimated based on the delivery time in the order demand information, the delivery duration obtained from the comprehensive score calculation step, the current time, and the final transportation duration. Specifically: determine the first time difference between the current time and the order delivery time; subtract the delivery duration from the first time difference to obtain the second time difference; retrieve the final transportation duration from the warehousing provider to the delivery location; subtract the final transportation duration from the second time difference to obtain the warehousing duration of the warehousing provider in the target candidate combination. The final transportation duration can be estimated by the difference between the distance from the warehousing provider to the delivery location and the transportation speed.

[0051] For transportation costs, the first transportation cost between the supplier and the manufacturer and the second transportation cost between the manufacturer and the warehouse are calculated separately. The first transportation cost = material transportation unit price × transportation distance × material weight, and the second transportation cost = product transportation unit price × transportation distance × product weight. Finally, the two are added together to obtain the total transportation cost.

[0052] This embodiment breaks down the overall cost into material, production, warehousing, and two-stage transportation costs, and calculates them item by item, comprehensively covering the cost composition of the entire upstream process of the supply chain, avoiding cost omissions, providing real and complete cost data support for comprehensive scoring, and improving the economic efficiency of decision-making.

[0053] In one possible implementation of this application, before determining the candidate combination with the highest comprehensive score as the optimal combination, the method further includes: For each candidate combination, a supply chain risk cost accounting factor is introduced, and the risk cost includes material shortage risk cost, production delay risk cost and inventory backlog risk cost. Based on historical risk data, the expected value of each risk cost is calculated using the Monte Carlo simulation method; Update the overall score of candidate combinations using the expected value.

[0054] Specifically, historical risk data for a recent period (e.g., 3 years) is retrieved from the system database, including material shortage risk data for each supplier, production delay risk data for each manufacturer, and inventory backlog risk data for each warehouse provider. Material shortage risk data includes the number of shortages, the amount of shortage, the amount of loss per incident, and the probability of occurrence; production delay risk data includes the duration of delays, the amount of loss per incident, and the probability of occurrence; and inventory backlog risk data includes the duration of backlog, the amount of loss per incident, and the probability of occurrence.

[0055] To address the cost of material shortage risk, based on historical shortage probabilities and loss amount distributions, a Monte Carlo random sampling method is used via a computer program. More than 10,000 simulation iterations are performed, with each iteration randomly generating the risk occurrence state and corresponding loss amount. After each iteration, the arithmetic mean of all simulation results is calculated to obtain the expected value of the material shortage risk cost. For the cost of production delay risk, the same simulation logic is used, employing iterative sampling based on historical production delay data to calculate the expected value of the production delay risk cost. For the cost of inventory backlog risk, Monte Carlo simulation iterations are performed, combining inventory backlog duration and loss probability distributions, to obtain the expected value of the inventory backlog risk cost.

[0056] Summarize the expected risk costs, and calculate the weighted sum of the expected costs of material shortage risk, production delay risk, and inventory backlog risk based on preset weights to obtain the total expected risk cost. Extract the total expected risk cost of all candidate combinations and determine the maximum and minimum total expected risk cost. Normalize the total expected risk cost of the target candidate combination to obtain the risk deduction score, calculated using the formula: Risk Deduction Score = (Total Expected Risk Cost of Target Candidate Combination - Minimum Expected Risk Cost) / (Maximum Expected Risk Cost - Minimum Expected Risk Cost) × 100.

[0057] Retrieve the original comprehensive score of the candidate combination before considering risk, and calculate the final updated comprehensive score using the formula: Final Comprehensive Score = Original Comprehensive Score - Risk Deduction Score × Risk Adjustment Weight. The risk adjustment weight can be flexibly set based on practical experience; this embodiment does not impose limitations. The calculated final comprehensive score overwrites the original score, updating the comprehensive score of the candidate combination. Perform the same operation on all candidate combinations sequentially to obtain the risk-adjusted comprehensive scores for all combinations. Sort all candidate combinations in descending order according to their updated final comprehensive scores, and select the candidate combination with the highest score as the optimal supply chain combination for this order, completing the selection of the optimal combination after risk adjustment.

[0058] This embodiment introduces multiple risk cost accounting factors before determining the optimal combination, uses Monte Carlo simulation to calculate the expected value of risk and update the comprehensive score, integrates the quantification of potential risks into the evaluation system, effectively reduces the probability of high-risk combinations being selected, and improves the overall stability and risk resistance of the supply chain.

[0059] One possible implementation of this application embodiment involves generating a list of orders to be shipped based on the order demand information of each order to be shipped, including: Extract the required delivery time and order priority from the order demand information of each order awaiting shipment; The system uses a multi-level sorting rule, with order priority as the first sorting criterion and required delivery time as the second sorting criterion, to generate a list of orders awaiting shipment.

[0060] In this embodiment, order priority is used as the primary sorting criterion. All orders awaiting shipment are sorted in ascending order of priority number, with high-priority (Level 1) orders at the top, medium-priority (Level 2) orders in the middle, and low-priority (Level 3) orders at the bottom. Within the same priority order group, delivery time is used as the secondary sorting criterion, and orders are sorted in ascending order of time, with earlier delivery times ranking higher. If an order has the same priority and delivery time, it is further sorted by order number in ascending order to ensure that the position of each order is unique and definite.

[0061] This embodiment uses order priority as the primary criterion and required delivery time as the secondary criterion to sort orders according to multi-level rules, quickly generating a list of orders to be shipped. This ensures that urgent orders are shipped first, while also meeting timeliness requirements, simplifying the sorting logic and taking into account both fulfillment efficiency and customer experience.

[0062] One possible implementation of this application embodiment involves determining the carrier for each order in the list of orders to be shipped, including: Simultaneously send transportation demand information to multiple candidate carriers corresponding to each order in the order list. The transportation demand information includes cargo attributes, planned loading time, delivery time window and planned transportation route. For each order awaiting shipment, receive quotation information from each candidate carrier, including transportation cost, planned transportation time, and available capacity; The matching degree between each candidate carrier and the corresponding order to be shipped is calculated based on the quotation information; For each order awaiting shipment, select the candidate carrier with the highest matching degree as the carrier.

[0063] In this embodiment, for each order in the pending outbound order list, multiple candidate carriers with corresponding transportation qualifications, sufficient capacity, route coverage, and timely delivery are selected from the carrier database based on the order's cargo attributes, transportation distance, delivery time window, and transportation route. Standardized transportation demand information is generated, clearly including: cargo attributes (cargo type, weight, volume, packaging form, and special transportation requirements), planned loading time (the time when the warehouse is determined to have the goods ready for loading), delivery time window (the earliest and latest delivery time interval required by the customer), planned transportation route (the preset route from the warehouse to the delivery location), order number, loading location, and delivery location. The transportation demand information is simultaneously sent to all candidate carriers corresponding to the order via system interfaces, message pushes, etc., and the sending time is recorded to ensure that all carriers receive the demand synchronously.

[0064] The system opens a quote receiving channel, receiving quote information from candidate carriers in real time. Each quote is linked to an order number and a carrier identifier to ensure a one-to-one correspondence. Quote information must include: transportation cost (total transportation cost, cost breakdown), planned transportation time (the carrier's promised time from loading completion to delivery to the destination), and available capacity (vehicle model, load capacity, and personnel configuration). Quote information is validated: the system checks for completeness, reasonableness of transportation costs, whether the planned transportation time meets the delivery window, and whether available capacity matches the cargo requirements. Invalid quotes with missing information or that do not meet the requirements are removed. Valid quotes that pass validation are categorized and stored, linked to the corresponding order and carrier, forming a quote dataset, awaiting matching degree calculation.

[0065] The matching score calculation includes dimensions such as transportation cost quotes, planned transportation time, and available capacity weights. The weights for these three dimensions can be flexibly set according to business scenarios, with a sum of 1. A reverse scoring method is used: lower transportation costs result in higher scores. Transportation costs for all candidate carriers are normalized to a score of 0-100 based on the maximum and minimum transportation costs. Shorter transportation times result in higher scores. Transportation times for all candidate carriers are normalized to a score of 0-100 based on the maximum and minimum transportation times. A positive scoring method is also used: a wider range of vehicle models, larger loading capacity, and more personnel result in higher scores. Corresponding scores can be set for different vehicle models, loading capacities, and personnel configurations, forming a pre-defined mapping table. The matching score is obtained by weighted summation of transportation cost quotes, planned transportation time, and available capacity.

[0066] For a single order awaiting shipment, all candidate carriers are sorted in descending order of their matching scores. The candidate carrier with the highest matching score is selected and marked as the final carrier for that order. If multiple carriers have the same matching score, the carrier with the shorter planned transit time is prioritized. If the transit times are the same, the carrier with the lower transit cost is selected, ensuring a unique selection. The binding relationship between the order and the final carrier is recorded, generating the carrier selection result and completing the carrier determination process for all orders awaiting shipment. This provides a basis for subsequently sending transit requests and executing transit tasks.

[0067] This embodiment simultaneously sends transportation requests to multiple candidate carriers, collects quotations, and calculates the matching degree to select the best carrier, thereby achieving fair bidding and intelligent matching of transportation resources. This improves capacity adaptability and delivery timeliness while controlling transportation costs.

[0068] One possible implementation of this application embodiment involves selecting multiple candidate combinations from supply chain participants that can satisfy order demand information, including: Obtain information on the capabilities of supply chain participants; Based on capability information and order demand information, filter candidate supplier subsets, candidate manufacturer subsets, and candidate warehousing subsets; The elements in the candidate supplier subset, candidate manufacturer subset, and candidate warehouse subset are combined to generate multiple candidate combinations.

[0069] In this embodiment, complete capability information of all registered supply chain participants is retrieved in batches from the supply chain resource database. Capability data of three types of participants are extracted: supplier capability information includes the types of materials that can be supplied, material specifications, material quality grades, maximum supply quantity, supply cycle, and supply geographical range; manufacturer capability information includes the types of products that can be produced, production process standards, minimum / maximum production capacity, production cycle, quality testing capabilities, and production geographical range; and warehousing capability information includes warehousing type, maximum warehousing capacity, specifications of goods that can be stored, sorting and outbound efficiency, warehousing geographical range, and delivery service capabilities.

[0070] The system iterates through the capabilities of all suppliers, comparing them item by item with the material categories, specifications, quality, supply quantity, supply cycle, and geographical requirements in the order requirements. Suppliers that meet all criteria are included in the candidate supplier subset, while those that do not meet any criteria are directly eliminated. Similarly, the system iterates through the capabilities of all manufacturers, comparing them item by item with the product categories, process standards, production capacity, production cycle, quality, and geographical requirements in the order requirements. Manufacturers that meet all criteria are included in the candidate manufacturer subset, while those that do not meet any criteria are directly eliminated. Finally, the system iterates through the capabilities of all warehousing providers, comparing them item by item with the warehousing type, capacity, goods specifications, outbound efficiency, geographical location, and delivery requirements in the order requirements. Warehouse providers that meet all criteria are included in the candidate warehouse provider subset, while those that do not meet any criteria are directly eliminated.

[0071] The combination rules are defined as follows: one supplier, one manufacturer, and one warehousing provider constitute a valid candidate combination. Each supplier is sequentially selected from the candidate supplier subset and paired with each manufacturer from the candidate manufacturer subset. Each pairing is then combined with each warehousing provider from the candidate warehousing provider subset to form a complete unit. All generated combinations are checked for duplicates to remove duplicates. Simultaneously, the geographical synergy and cooperation compatibility of the entities within each combination are verified, and invalid combinations that cannot actually collaborate are removed. All valid, unique combinations are compiled to form a candidate combination set, completing the generation of multiple candidate combinations, awaiting subsequent comprehensive score calculation.

[0072] This embodiment first obtains the capability information of each participant and filters out three qualified candidate subsets, and then combines them to generate candidate solutions, ensuring that all combinations meet the basic requirements of the order, narrowing the optimization scope, and improving the efficiency and effectiveness of subsequent comprehensive scoring and selection of the best combination.

[0073] This application provides a supply chain management system, such as... Figure 2 As shown, the system includes a receiving module 201, a first determining module 202, a generating module 203, and a second determining module 204, wherein: The receiving module 201 is used to receive order demand information uploaded by the client and select multiple candidate combinations from the supply chain participants that can meet the order demand information. Each candidate combination includes a supplier, a manufacturer, and a warehouse. The first determining module 202 is used to determine the comprehensive score of each candidate combination and determine the candidate combination with the highest comprehensive score as the best combination. The generation module 203 is used to obtain the outbound orders of the warehouse in the best combination and generate a list of outbound orders based on the order demand information of each outbound order. The second determining module 204 is used to determine the carrier for each order to be shipped in the order list and send the transportation request for each order to be shipped to the corresponding carrier to guide the execution of the transportation task.

[0074] This application provides an electronic device, such as... Figure 3 As shown, Figure 3 The illustrated electronic device 300 includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of this electronic device 300 does not constitute a limitation on the embodiments of this application.

[0075] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0076] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0077] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0078] The memory 303 stores the application code that executes the solution of this application, and its execution is controlled by the processor 301. The processor 301 executes the application code stored in the memory 303 to implement the content shown in the aforementioned supply chain management method embodiment.

[0079] Figure 3 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0080] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the contents shown in the aforementioned supply chain management method embodiments.

[0081] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0082] This application provides a computer program product, including a computer program that, when executed by a processor, implements the content shown in the aforementioned supply chain management method embodiment.

[0083] The above are only some embodiments of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A supply chain management method, characterized in that, include: The system receives order demand information uploaded by the client and selects multiple candidate combinations from supply chain participants that can meet the order demand information. Each candidate combination includes a supplier, a manufacturer, and a warehouse provider. Determine the comprehensive score for each candidate combination, and determine the candidate combination with the highest comprehensive score as the best combination; Obtain the outbound orders from the warehouse in the optimal combination, and generate an outbound order list based on the order demand information of each outbound order; The carrier for each order in the list of orders to be shipped is determined, and the transportation request for each order is sent to the corresponding carrier to guide the execution of the transportation task.

2. The supply chain management method according to claim 1, characterized in that, Determining the comprehensive score for each candidate combination includes: Determine the overall cost, performance reliability, and delivery time of the target candidate combination, wherein the target candidate combination is any one of the plurality of candidate combinations; The maximum and minimum comprehensive costs are determined from the comprehensive costs of the multiple candidate combinations, and the maximum and minimum delivery times are determined from the delivery times of the multiple candidate combinations. The pre-built comprehensive score calculation model is invoked, and the maximum comprehensive cost, the minimum comprehensive cost, the maximum delivery time, the minimum delivery time, and the comprehensive cost, performance reliability, and delivery time of the target candidate combination are substituted into the comprehensive score calculation model to obtain the comprehensive score of the target candidate combination.

3. The supply chain management method according to claim 2, characterized in that, Determining the overall cost of the target candidate combination includes: Determine the material costs of suppliers, the production costs of manufacturers, and the warehousing costs of warehouse providers in the target candidate combinations; Determine the first transportation cost between the supplier and the manufacturer and the second transportation cost between the manufacturer and the warehouse in the target candidate combination, and calculate the sum of the first transportation cost and the second transportation cost to obtain the transportation cost; The sum of the material cost, the production cost, the warehousing cost, and the transportation cost is calculated to obtain the comprehensive cost of the target candidate combination.

4. The supply chain management method according to claim 1, characterized in that, Before determining the candidate combination with the highest comprehensive score as the optimal combination, the method further includes: For each candidate combination, a supply chain risk cost accounting factor is introduced, and the risk cost includes material shortage risk cost, production delay risk cost and inventory backlog risk cost. Based on historical risk data, the expected value of each risk cost is calculated using the Monte Carlo simulation method; The overall score of the candidate combination is updated using the expected value.

5. The supply chain management method according to claim 1, characterized in that, Determining the carrier for each order in the list of orders to be shipped includes: Simultaneously send transportation demand information to multiple candidate carriers corresponding to each order in the order list to be shipped out, the transportation demand information including cargo attributes, planned loading time, delivery time window and planned transportation route; For each order to be shipped, receive quotation information from each candidate carrier, including transportation cost quotes, planned transportation time, and available transportation capacity; Based on the quoted information, the matching degree between each candidate carrier and the corresponding order to be shipped is calculated; For each order awaiting shipment, select the candidate carrier with the highest matching degree as the carrier.

6. The supply chain management method according to claim 1, characterized in that, The selection of multiple candidate combinations from supply chain participants that can meet the order requirements includes: Obtain the capability information of the aforementioned supply chain participants; Based on the capability information and the order demand information, a subset of candidate suppliers, a subset of candidate manufacturers, and a subset of candidate warehousing providers are selected; The elements of the candidate supplier subset, the candidate manufacturer subset, and the candidate warehousing subset are combined to generate multiple candidate combinations.

7. The supply chain management method according to claim 1, characterized in that, A list of orders to be shipped is generated based on the order demand information of each order to be shipped, including: Extract the required delivery time and order priority from the order demand information of each order awaiting shipment; The order list to be shipped is generated by sorting the orders according to a multi-level rule based on the order priority as the first sorting criterion and the required delivery time as the second sorting criterion.

8. A supply chain management system, characterized in that, include: The receiving module is used to receive order demand information uploaded by the client and select multiple candidate combinations from the supply chain participants that can meet the order demand information. Each candidate combination includes a supplier, a manufacturer, and a warehouse. The first determining module is used to determine the comprehensive score of each candidate combination, and to determine the candidate combination with the highest comprehensive score as the best combination; The generation module is used to obtain the outbound orders of the warehouse in the optimal combination, and generate a list of outbound orders based on the order demand information of each outbound order. The second determining module is used to determine the carrier for each outbound order in the list of outbound orders, and send the transportation request for each outbound order to the corresponding carrier to guide the execution of the transportation task.

9. An electronic device, characterized in that, include: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, said at least one application being configured to: perform the supply chain management method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed in a computer, the computer is instructed to perform the supply chain management method according to any one of claims 1-7.

Images