Improved variable neighborhood search algorithm for multi-compartment green vehicle routing problem

被引：0
作者：
Xiao Y.-G. [1 ]
Cao J. [1 ]
Chen W.-R. [1 ]
Zhang D.-Z. [1 ]
Li S.-Y. [2 ]
机构：
[1] College of Transportation Engineering, Central South University, Hunan, Changsha
[2] College of Logistics and Transportation, Central South University of forestry science and technology, Hunan, Changsha
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2024年 / 41卷 / 04期
基金：
中国国家自然科学基金;
关键词：
balanced shaking; granular mechanism; green vehicle routing; improved variable neighborhood search; multi-compartment distribution;
D O I：
10.7641/CTA.2023.20182
中图分类号：
学科分类号：
摘要：
Focusing on the problem of “multiple depots, punctuality, multiple products and energy intensity” arising in the distribution scenario of community group purchase, this paper studies the multi-depot multi-compartment green vehicle routing problem with time windows (MDMCGVRPTW). A mixed integer linear programming (MILP) model and an improved variable neighborhood search (IVNS) algorithm are proposed. High quality initial solutions are obtained by a two-stage hybrid (2SH) algorithm. A new balanced shaking heuristic is designed to fully explore the solution space, and a granularity mechanism is introduced to improve the efficiency of local search. The 2SH algorithm and the IVNS algorithm have already demonstrated their effectiveness in solving the benchmarks. The experiment results based on the simulation examples show that the proposed model and algorithm can effectively solve the MDMCGVRPTW, and the improved strategies enhance the exploitation capability of the IVNS algorithm. Finally, some management insights for relevant distribution enterprises are given based on the sensitivity analysis of distribution strategy and timeliness to achieve cost reduction and efficiency increase. © 2024 South China University of Technology. All rights reserved.
引用
收藏
页码：751 / 762
页数：11
相关论文
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