Research on the Two-Stage Vehicle Routing Problem of Returned Logistics Recycling of Waste Electrical

This article focuses on the problem of returned logistics recycling of waste electrical, and proposes an improved vehicle routing problem model considering the packing and a decision-making model for the location and layout of waste electrical recycling networks. To solve the problem of reverse logistics recycling of waste electrical, a two-stage vehicle routing problem decision-making model is established to optimize the optimal layout scheme of secondary network, to achieve the goal of the minimize carbon emission and total transportation cost under multiple scenarios. The particle swarm optimization is designed to solve the practical problems of large, medium and small scales. From the experimental results, it is found that the cost of the original plan in all experiments is higher than the result solved by the optimized decision-making model.

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Publication Details

Published
2024-08-29
DOI
https://doi.org/10.1109/icsece61636.2024.10729497
Primary Topic
Recycling and Waste Management Techniques
Type
article
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article

Research on the Two-Stage Vehicle Routing Problem of Returned Logistics Recycling of Waste Electrical

Wenxin Li, Shihong Jiang
Recycling and Waste Management Techniques
article

Research on the Two-Stage Vehicle Routing Problem of Returned Logistics Recycling of Waste Electrical

Wenxin Li, Shihong Jiang
article en

Abstract

This article focuses on the problem of returned logistics recycling of waste electrical, and proposes an improved vehicle routing problem model considering the packing and a decision-making model for the location and layout of waste electrical recycling networks. To solve the problem of reverse logistics recycling of waste electrical, a two-stage vehicle routing problem decision-making model is established to optimize the optimal layout scheme of secondary network, to achieve the goal of the minimize carbon emission and total transportation cost under multiple scenarios. The particle swarm optimization is designed to solve the practical problems of large, medium and small scales. From the experimental results, it is found that the cost of the original plan in all experiments is higher than the result solved by the optimized decision-making model.

Shanghai University (CN)
Openalex Percentile: Top 77%
Recycling and Waste Management Techniques
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