吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (2): 631-638.doi: 10.13229/j.cnki.jdxbgxb.20231452

• 交通运输工程·土木工程 • 上一篇    

基于多目标蚁群算法的多配送中心应急物资配送车辆调度优化方法

刘建辉(),王琼   

  1. 西安建筑科技大学 机电学院,西安 710055
  • 收稿日期:2023-12-28 出版日期:2025-02-01 发布日期:2025-04-16
  • 作者简介:刘建辉(1976-),男,副教授,博士.研究方向:新能源发电及机器人控制技术.|E-mail:ljianhui20230@163.com
  • 基金资助:
    国家青年科学基金项目(52206109)

Optimization method for emergency material delivery vehicle scheduling in multiple distribution centers based on multi-objective ant colony algorithm

Jian-hui LIU(),Qiong WANG   

  1. School of Mechanical and Electrical Engineering,Xi'an University of Architecture&Technology,Xi 'an 710055,China
  • Received:2023-12-28 Online:2025-02-01 Published:2025-04-16

摘要:

为有效解决多配送中心应急物资配送车辆调度方案不佳和物资满意度低的问题,提出了一种基于多目标蚁群算法的多配送中心应急物资配送车辆调度优化方法。考虑到配送路径的实际情况,以车辆平均运输时间和物资满足度最大化为目标,构建多配送中心应急物资配送车辆调度优化多目标函数。结合多目标蚁群算法对多目标函数求解,确定最优多配送中心应急物资配送车辆调度方案。实验分析证明:本文方法的多配送中心应急物资配送方案更加合理,调度综合系数在0.950以上,并且物资满意度达到了90.00%以上,其有效提高了车辆调度效果,能够制订更加合理的调度方案。

关键词: 多目标蚁群算法, 多配送中心, 应急物资配送, 车辆调度优化

Abstract:

In order to effectively solve the problems of poor vehicle scheduling scheme and low satisfaction of materials in multi-distribution center, a multi-objective ant colony algorithm based vehicle scheduling optimization method for multi-distribution center emergency materials distribution was proposed. Considering the actual situation of the distribution route, aiming at maximizing the average transportation time and material satisfaction, the multi-objective function of vehicle scheduling optimization for emergency materials distribution in multi-distribution centers was constructed. Based on the multi-objective ant colony algorithm, the optimal vehicle scheduling scheme for emergency materials distribution in multi-distribution center is determined. The experimental analysis proves that the proposed multi-distribution center emergency materials distribution scheme is more reasonable, the scheduling comprehensive coefficient is above 0.950, and the material satisfaction rate is above 90.00%, which effectively improves the vehicle scheduling effect and can develop a more reasonable scheduling scheme.

Key words: multi objective ant colony algorithm, multiple distribution centers, emergency material distribution, vehicle scheduling optimization

中图分类号: 

  • F252

图1

配送中心和受灾点分布"

表1

配送车辆调度优化方法参数"

序号参数数值
1uik100
2k10
3M1.024
4α1.143
5ρ(0,1)
6ε0.651

表2

多目标蚁群算法求解可行解结果"

测试指标预期目标多目标蚁群算法
平均最优解1 7021 578
最优解/车辆数1 464/41 355/3
平均解1 7791 635
平均偏差0.1770.171
最大偏差0.2630.224
运算时间/s46.8241.55
平均运算时间/s40.1137.25

图2

不同方法的多配送中心应急物资配送车辆调度方案比较"

表3

多配送中心应急物资配送车辆调度方案调度综合系数"

调度方案调度综合系数
本文方法文献[3]方法文献[4]方法
10.9570.9120.845
20.9710.9050.901
30.9590.9110.867

图3

不同调度方法的物资满足率比较"

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