现代电子技术2024，Vol.47Issue(7)：181-186,6.DOI:10.16652/j.issn.1004-373x.2024.07.032
基于改进的蚁群算法的目标物流车辆路径优化
Target logistics vehicle path optimization based on improved ant colony optimization algorithm
摘要
Abstract
With the development of cold chain logistics,the route optimization of logistics vehicles has gradually appeared in the public's vision.However,the transportation cost and route have been troubling logistics companies.In view of this,the route optimization of cold chain logistics vehicles is proposed.The following two aspects are mainly designed.By establishing a cold chain logistics model,the model is established by taking account of the carbon emission cost and vehicle transportation cost.By the research on the improved ant colony optimization(IACO)algorithm,the optimal and worst ACO algorithm and heuristic factor algorithm are introduced to establish the path optimization model.The traditional ACO algorithm and the IACO algorithm can shorten the vehicle driving path,and the ACO algorithm can improve the convergence and optimize the vehicle driving path.The results show that the IACO algorithm can optimize the route and reduce the transportation cost,which is better than that of the traditional ACO algorithm,so the improved algorithm can enhance the transportation efficiency of the company.关键词
冷链物流/改进蚁群算法/优化路线/提升收敛性/降低运输成本/提高运输效率Key words
cold chain logistics/IACO algorithm/route optimization/convergence improvement/transportation cost reduction/transportation efficiency enhancement分类
信息技术与安全科学引用本文复制引用
曾胜,王兵,戴贤君..基于改进的蚁群算法的目标物流车辆路径优化[J].现代电子技术,2024,47(7):181-186,6.基金项目
国家自然科学基金资助项目(62172004) （62172004）
安徽高校研究项目(2022AH052433) （2022AH052433）
衢州市科技计划项目(2022K26) （2022K26）
