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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
06.02.2025
DOI
https://doi.org/10.7307/ptt.v37i1.578
ISSUE
2025 (Vol 37), Issue 1
LICENSE
Copyright (c) 2025 Xiaojuan LU, Jianjun WANG, Shuai WU, Shiyu ZHENG, Qian LIU
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This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

Two-Echelon Location-Routing Problem with Fuzzy Demand of Rural E-Commerce Logistics

Authors:Xiaojuan LU, Jianjun WANG, Shuai WU, Shiyu ZHENG, Qian LIU

Abstract

To promote the green and high-quality development of rural e-commerce logistics, we propose the Two-Echelon Location-Routing Problem with Fuzzy Demand (2E-LRP-FD) of the rural e-commerce logistics network. Considering fuzzy demand, government subsidies and simultaneous delivery, the objective function aims to maximise the profit of enterprises considering government subsidies. The fuzzy chance-constrained programming method is used to deal with the triangular fuzzy variables of pickup demands. Additionally, we present a two-stage Improved Non-Dominated Sorting Genetic Algorithm II (INSGA-II) that integrates stochastic simulation and a K-means clustering algorithm to effectively solve the problem. In the end, the numerical experiments of algorithm and model design are verified. The experimental results demonstrate that the proposed INSGA-II is significantly efficient and effective. Furthermore, we discuss the relationship between subsidy strategies and logistics enterprise profits. This research contributes valuable insights for the establishment of rural e-commerce logistics systems.

Keywords:two-echelon location-routing problem, fuzzy demand, k-means clustering, improved NSGA-II, rural e-commerce logistics

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