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考虑充电策略的冷链物流配送路径优化研究

王嘉宁 初良勇

计算机工程与应用2024,Vol.60Issue(17):282-292,11.
计算机工程与应用2024,Vol.60Issue(17):282-292,11.DOI:10.3778/j.issn.1002-8331.2401-0350

考虑充电策略的冷链物流配送路径优化研究

Route Optimization of Cold Chain Logistics and Distribution Paths for Considering Charging Strategies

王嘉宁 1初良勇2

作者信息

  • 1. 集美大学 航海学院,福建 厦门 361021
  • 2. 集美大学 航海学院,福建 厦门 361021||福建航运研究院,福建 厦门 361021
  • 折叠

摘要

Abstract

With the requirements of green and sustainable development,the use of electric logistics vehicles for cold chain logistics and distribution has gradually become a hotspot.Under the consideration of constraints such as charging strategy,vehicle loading,and customer time window,a path optimization model of electric vehicles in cold chain logistics and distribution with the objective of minimizing the total cost of distribution is constructed.According to the characteristics of the designed model,a hybrid algorithm combining marine predator and ant colony algorithm is proposed for solving,which effectively improves the searching ability and global information capture.According to the comparison of the analyses of the algorithms,it can be seen that considering the charging strategy and thus not charging the vehicle to full charge can reasonably utilize the vehicle resources and effectively reduce the logistics cost by 17.34%compared with the fully charging strategy.It analyzes the impact of maximum vehicle load on the total logistics cost by setting the maximum vehi-cle load,so as to provide enterprises with different vehicle choices.By utilizing actual cases and specific data for experi-ments,this verifies that the model constructed is effective and proves the efficiency of the algorithm.

关键词

城市交通/车辆路径问题(VRP)/蚁群算法(ACO)/海洋捕食者算法(MPA)/充电策略

Key words

urban traffic/vehicle routing problem(VRP)/ant colony optimization(ACO)/marine predators algorithm(MPA)/charging strategy

分类

交通工程

引用本文复制引用

王嘉宁,初良勇..考虑充电策略的冷链物流配送路径优化研究[J].计算机工程与应用,2024,60(17):282-292,11.

基金项目

国家社科基金重大项目(23&ZD138). (23&ZD138)

计算机工程与应用

OA北大核心CSTPCD

1002-8331

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