EPR supply chain management method and system based on big data

Abstract

The invention provides an EPR supply chain management method and system based on big data. The method comprises the steps that current position information and life cycle information of at least one to-be-recycled product are determined; according to the current position information and the life cycle information, recycling position information of all the to-be-recycled products is determined; inputting the current position information and the recovery position information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; and based on the reverse logistics path, the to-be-recycled product is recycled. A plurality of recovery points are set, corresponding recovery position information is selected according to current position information and life cycle information of a to-be-recovered product, a reverse logistics path is determined based on a reverse logistics path planning model, and a final recovery position of the product is determined before the to-be-recovered product is recovered, so that the recovery efficiency is improved. And additional storage cost and logistics cost are prevented from being increased.

Description

Technical Field

[0001] The present invention relates to the field of supply chain technology, and in particular to an EPR supply chain management method and system based on big data. Background Art

[0002] An EPR (Extended Producer Responsibility) supply chain refers to a system in which producers assume greater responsibility for product lifecycle management, such as product recycling, remanufacturing, and waste disposal. Currently, product recycling typically involves bringing products to a centralized location, where they are manually sorted and their final destination determined. This results in low recycling efficiency and incurs additional storage costs. If the final destination of recycled products is inconsistent with the centralized recycling location, additional logistics costs are also incurred. Summary of the Invention

[0003] The present invention provides an EPR supply chain management method and system based on big data, which improves product recovery efficiency and reduces costs.

[0004] The present invention provides an EPR supply chain management method based on big data, comprising: Determining current location information and life cycle information of at least one product to be recycled; Determining recycling location information of each of the products to be recycled based on the current location information and the life cycle information; Inputting the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; The product to be recycled is recycled based on the reverse logistics path.

[0005] According to a big data-based EPR supply chain management method provided by the present invention, determining the current location information and life cycle information of at least one product to be recycled includes: In response to a product recall request, parsing the product recall request; Determining whether the product recycling request includes the current location information and life cycle information of the product to be recycled; If the product recycling request does not include the current location information and the life cycle information of the product to be recycled, the current location information and the life cycle information are determined based on historical data of the product to be recycled.

[0006] According to a big data-based EPR supply chain management method provided by the present invention, determining the recycling location information of each of the products to be recycled based on the current location information and the life cycle information includes: Determining whether the product to be recycled can be recycled based on the life cycle information; If the products to be recycled cannot be recycled, the recycling location information of each of the products to be recycled is determined based on the current location information.

[0007] According to the present invention, a big data-based EPR supply chain management method further includes: If the product to be recycled is recyclable, determining a candidate recycling location that matches the life cycle information; The recycling location information of each of the products to be recycled corresponding to the current location information is obtained by screening the candidate recycling locations.

[0008] According to a big data-based EPR supply chain management method provided by the present invention, the reverse logistics path planning model includes: a path generating unit, configured to generate a candidate path set based on the current location information and the recycling location information; A path screening unit is used to select the reverse logistics path from the candidate path set based on the constraint conditions corresponding to the life cycle information.

[0009] According to the EPR supply chain management method based on big data provided by the present invention, the reverse logistics path planning model further includes: The path optimization unit is configured to optimize the candidate paths in the candidate path set.

[0010] The present invention also provides an EPR supply chain management system based on big data, comprising: A first determination model is used to determine current location information and life cycle information of at least one product to be recycled; A second determining module is configured to determine the recycling location information of each of the products to be recycled based on the current location information and the life cycle information; a planning module, configured to input the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; A recycling module is used to recycle the product to be recycled based on the reverse logistics path.

[0011] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the EPR supply chain management method based on big data as described above is implemented.

[0012] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described EPR supply chain management methods based on big data.

[0013] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-described EPR supply chain management methods based on big data.

[0014] The big data-based EPR supply chain management method and system provided by the present invention set up multiple recycling points, select corresponding recycling location information based on the current location information and life cycle information of the product to be recycled, determine the reverse logistics path based on the reverse logistics path planning model, and determine the final recycling location of the product before the product to be recycled, thereby improving recycling efficiency and avoiding additional warehousing and logistics costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 It is a flow chart of the EPR supply chain management method based on big data provided by the present invention; Figure 2 It is a structural diagram of the EPR supply chain management system based on big data provided by the present invention; Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0017] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0018] It should be noted that, in the description of the present invention, the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, the phrase "comprises a..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising the elements. Terms such as "upper" and "lower" indicate positions or relationships based on those shown in the accompanying drawings and are intended solely to facilitate the description of the present invention and simplify the description. They are not intended to indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation, and are therefore not to be construed as limitations on the present invention. Unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be broadly construed, for example, to mean fixed, removable, or integral; mechanical or electrical; direct or indirect through an intermediary; or internal communication between two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0019] The terms "first," "second," and so forth, used herein are used to distinguish similar objects, not to describe a specific order or precedence. It should be understood that such terms are interchangeable where appropriate, allowing embodiments of the present invention to be implemented in an order other than that illustrated or described herein. Furthermore, the terms "first," "second," and so forth generally distinguish objects of a single type, and do not limit the number of objects. For example, the first object may be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the connected objects.

[0020] Figure 1 This is a flow chart of the EPR supply chain management method based on big data provided by the present invention, such as Figure 1 As shown, the present invention provides an EPR supply chain management method based on big data, comprising the following steps: Step S100: determining the current location information and life cycle information of at least one product to be recycled.

[0021] Products involved in the EPR (Extended Producer Responsibility) supply chain are typically those subject to environmental regulations and requiring producers to be responsible for their entire lifecycle, particularly recycling and disposal. Common products include electronic and electrical products, packaging materials, batteries and accumulators, automotive products, chemicals, and hazardous waste.

[0022] The life cycle of products in the EPR supply chain includes the product design stage, production and manufacturing stage, distribution and circulation stage, consumption and use stage, and recycling and processing stage. The recycled products provided by the present invention may be in the distribution and circulation stage, consumption and use stage, or recycling and processing stage. Products in the distribution and circulation stage and the consumption and use stage can be directly redistributed and circulated without processing, while products in the recycling and processing stage must be graded and harmlessly treated before they can re-enter the distribution and circulation stage.

[0023] The present invention determines whether the product can enter the distribution and circulation stage directly or enter the distribution and circulation stage after recycling by confirming the current location information and life cycle information of the product to be recycled. It should be noted that for products that cannot be redistributed, they should be processed directly according to the requirements.

[0024] Step S200: determining the recycling location information of each of the products to be recycled based on the current location information and the life cycle information.

[0025] Optionally, determining the recycling location information of each of the products to be recycled based on the current location information and the life cycle information includes: Determining whether the product to be recycled can be recycled based on the life cycle information; If the products to be recycled cannot be recycled, the recycling location information of each of the products to be recycled is determined based on the current location information.

[0026] Optionally, determining the recycling location information of each of the products to be recycled based on the current location information and the life cycle information further includes: If the product to be recycled is recyclable, determining a candidate recycling location that matches the life cycle information; The recycling location information of each of the products to be recycled corresponding to the current location information is obtained by screening the candidate recycling locations.

[0027] Specifically, the present invention sets at least one product recycling point for products at different life cycle stages. On this basis, multiple product recycling points are set for products at the same life cycle stage according to geographical location to reduce logistics costs and improve recycling efficiency.

[0028] Determining the recycling location information of each of the products to be recycled based on the current location information and the life cycle information specifically involves screening, based on the current location information and the life cycle information, from all product recycling points to obtain location information of a matching product recycling point that meets preset conditions. The preset conditions may be optimal cost, highest efficiency, or the like.

[0029] Step S300: input the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model.

[0030] The reverse logistics path planning model includes candidate reverse logistics paths for different life cycle stages and different product recycling points. For recycled products that can directly enter the distribution and circulation stages, the reverse logistics path can be output with the highest efficiency as the goal. The final destination of the reverse logistics path is the geographical location corresponding to the recycling location information. For recycled products in the recycling and processing stage, the final destination of the reverse logistics path may not completely match the geographical location corresponding to the recycling location information.

[0031] Step S400: Recycling the product to be recycled based on the reverse logistics path. After determining the reverse logistics path, the reverse logistics path is distributed to relevant personnel to recycle the product to be recycled.

[0032] Optionally, determining the current location information and life cycle information of at least one product to be recycled includes: Step S110 : In response to the product recycling request, the product recycling request is parsed.

[0033] Step S120 , determining whether the product recycling request includes the current location information and life cycle information of the product to be recycled.

[0034] Step S130: If the product recycling request does not include the current location information and life cycle information of the product to be recycled, determine the current location information and the life cycle information based on historical data of the product to be recycled.

[0035] A product recall request can be a consumer's proactive return of a product and a request for product recall from the manufacturer, or it can be a distributor or retailer's request for product recall from the manufacturer.

[0036] Consumers, distributors, or retailers can initiate a product recall request through a company's official website, app, or third-party recycling platform. Preferably, consumers, distributors, or retailers can also initiate a product recall request based on a product purchase order. If a consumer, distributor, or retailer initiates a product recall request through a company's official website, app, or third-party recycling platform, they must enter the current location and lifecycle information in the request. If the request is based on a product purchase order, they can choose whether to enter the current location and lifecycle information. Distributors or retailers can also initiate a product recall request through the EPR supply chain management system. At a minimum, they must enter the product's unique identifier in the request.

[0037] For product recall requests initiated based on a purchase order without the current location and lifecycle information, or for distributors or retailers initiating a product recall request through the EPR supply chain management system and only providing the product's unique identifier, the current location and lifecycle information can be determined based on the purchase order and the EPR supply chain management system database. Specifically, the current location information is the delivery address in the purchase order and the product registration location in the EPR supply chain management system. The lifecycle information is determined based on the time interval between the purchase order and the current time, and the time interval between the EPR supply chain management system's warehouse departure time and the current time.

[0038] As an optional embodiment, the reverse logistics path planning model includes: a path generating unit, configured to generate a candidate path set based on the current location information and the recycling location information; Based on the current location information and the recycling location information, a candidate path set is generated, specifically including: determining whether the recycling location information is the location information of a product recycling point; if not, using the current location information as the starting point and the recycling location information as the destination, calling a map APP interface, obtaining a path generated by the map APP, and obtaining a candidate path set.

[0039] If the recycling location information is location information of a product recycling point, multiple candidate paths are generated according to the recycling specification of the product recycling point as a candidate path set.

[0040] Specifically, the road network is represented as a weighted directed graph G =( V , E ), where: node set V stands for Road intersections, key landmarks, edge sets E stands for Road segment, each edge EUV Contains weights: w uv = α⋅distance uv + β ⋅time uv + γ ⋅cost uv , α, β, γ is a weight coefficient determined based on the recycling specifications of the product recycling point.

[0041] Set up the first i Path Pi The weight sum:

[0042] Path deviation (used to screen diversity) is expressed as:

[0043] Finding multiple paths using Dijkstra's algorithm P， For i = 2 to k: For each edge e in P1, ..., Pi−1, generate a candidate path: remove edge e, find the path of the remaining graph, and choose the new path with the smallest weight as Pi.

[0044] Optionally, the reverse logistics path planning model further includes: The path optimization unit is configured to optimize the candidate paths in the candidate path set. Specifically, a 2-opt algorithm may be applied to each path to reduce intersections.

[0045] A path screening unit is configured to select the reverse logistics path from the candidate path set based on constraints corresponding to the lifecycle information. The constraints corresponding to the lifecycle information may be optimal cost, highest efficiency, etc. For example, the constraint for the distribution and circulation stage and the consumption and use stage is highest efficiency, and the constraint for the recycling and processing stage is optimal cost.

[0046] The following describes the EPR supply chain management system based on big data provided by the present invention. The EPR supply chain management system based on big data described below and the EPR supply chain management method based on big data described above can refer to each other.

[0047] Figure 2 This is a schematic diagram of the structure of the EPR supply chain management system based on big data provided by the present invention, such as Figure 2 As shown, the present invention also provides an EPR supply chain management system based on big data, including: A first determination model 210 is used to determine the current location information and life cycle information of at least one product to be recycled; A second determining module 220 is configured to determine the recycling location information of each of the products to be recycled based on the current location information and the life cycle information; A planning module 230 is configured to input the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; The recycling module 240 is configured to recycle the product to be recycled based on the reverse logistics path.

[0048] As an embodiment, determining the current location information and life cycle information of at least one product to be recycled includes: In response to a product recall request, parsing the product recall request; Determining whether the product recycling request includes the current location information and life cycle information of the product to be recycled; If the product recycling request does not include the current location information and the life cycle information of the product to be recycled, the current location information and the life cycle information are determined based on historical data of the product to be recycled.

[0049] As an embodiment, determining the recycling location information of each of the products to be recycled based on the current location information and the life cycle information includes: Determining whether the product to be recycled can be recycled based on the life cycle information; If the products to be recycled cannot be recycled, the recycling location information of each of the products to be recycled is determined based on the current location information.

[0050] As an embodiment, it also includes: If the product to be recycled is recyclable, determining a candidate recycling location that matches the life cycle information; The recycling location information of each of the products to be recycled corresponding to the current location information is obtained by screening the candidate recycling locations.

[0051] As an embodiment, the reverse logistics path planning model includes: a path generating unit, configured to generate a candidate path set based on the current location information and the recycling location information; A path screening unit is used to select the reverse logistics path from the candidate path set based on the constraint conditions corresponding to the life cycle information.

[0052] As an embodiment, the reverse logistics path planning model further includes: The path optimization unit is configured to optimize the candidate paths in the candidate path set.

[0053] Figure 3 An example of a physical structure diagram of an electronic device is shown below. Figure 3As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the EPR supply chain management method based on big data, which includes: Determining current location information and life cycle information of at least one product to be recycled; Determining recycling location information of each of the products to be recycled based on the current location information and the life cycle information; Inputting the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; The product to be recycled is recycled based on the reverse logistics path.

[0054] Furthermore, the logic instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0055] On the other hand, the present invention further provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the EPR supply chain management method based on big data provided by the above methods, which includes: Determining current location information and life cycle information of at least one product to be recycled; Determining recycling location information of each of the products to be recycled based on the current location information and the life cycle information; Inputting the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; The product to be recycled is recycled based on the reverse logistics path.

[0056] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the EPR supply chain management method based on big data provided by the above methods, the method comprising: Determining current location information and life cycle information of at least one product to be recycled; Determining recycling location information of each of the products to be recycled based on the current location information and the life cycle information; Inputting the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; The product to be recycled is recycled based on the reverse logistics path.

[0057] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0058] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0059] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A big data-based EPR supply chain management method, characterized in that: include: Determining current location information and life cycle information of at least one product to be recycled; Determining recycling location information of each of the products to be recycled based on the current location information and the life cycle information; Inputting the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; The product to be recycled is recycled based on the reverse logistics path.

2. The EPR supply chain management method based on big data according to claim 1, characterized in that: The determining of the current location information and life cycle information of at least one product to be recycled includes: In response to a product recall request, parsing the product recall request; Determining whether the product recycling request includes the current location information and life cycle information of the product to be recycled; If the product recycling request does not include the current location information and the life cycle information of the product to be recycled, the current location information and the life cycle information are determined based on historical data of the product to be recycled.

3. The EPR supply chain management method based on big data according to claim 1, characterized in that: The determining, based on the current location information and the life cycle information, the recycling location information of each of the products to be recycled includes: Determining whether the product to be recycled can be recycled based on the life cycle information; If the products to be recycled cannot be recycled, the recycling location information of each of the products to be recycled is determined based on the current location information.

4. The EPR supply chain management method based on big data according to claim 3 is characterized in that: Also includes: If the product to be recycled is recyclable, determining a candidate recycling location that matches the life cycle information; The recycling location information of each of the products to be recycled corresponding to the current location information is obtained by screening the candidate recycling locations.

5. The EPR supply chain management method based on big data according to claim 1 is characterized in that: The reverse logistics path planning model includes: a path generating unit, configured to generate a candidate path set based on the current location information and the recycling location information; A path screening unit is used to select the reverse logistics path from the candidate path set based on the constraint conditions corresponding to the life cycle information.

6. The EPR supply chain management method based on big data according to claim 5 is characterized in that: The reverse logistics path planning model also includes: The path optimization unit is configured to optimize the candidate paths in the candidate path set.

7. An EPR supply chain management system based on big data, characterized in that: include: A first determination model is used to determine current location information and life cycle information of at least one product to be recycled; A second determining module is configured to determine the recycling location information of each of the products to be recycled based on the current location information and the life cycle information; a planning module, configured to input the current location information and the recycling location information into a preset reverse logistics path planning model to obtain a reverse logistics path output by the reverse logistics path planning model; A recycling module is used to recycle the product to be recycled based on the reverse logistics path.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the EPR supply chain management method based on big data as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the EPR supply chain management method based on big data as described in any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the EPR supply chain management method based on big data as described in any one of claims 1 to 6 is implemented.

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