上海交通大学学报 ›› 2019, Vol. 53 ›› Issue (8): 1000-1009.doi: 10.16183/j.cnki.jsjtu.2019.08.016
范厚明a,b,徐振林a,b,李阳a,刘文琪a,耿静a
出版日期:
2019-08-28
发布日期:
2019-09-10
作者简介:
范厚明(1962-),男,山东省蓬莱市人,教授,博士生导师,主要从事交通运输规划与管理等研究.
电话(Tel.):0411-84725868;E-mail:fhm468@163.com.
基金资助:
FAN Houming a,b,XU Zhenlin a,b,LI Yang a,LIU Wenqi a,GENG Jing a
Online:
2019-08-28
Published:
2019-09-10
摘要: 针对传统遗传算法在求解多中心车辆路径问题时存在:传统编解码方式引起的染色体长度不固定导致计算效率低下和易产生不可行解;扰动过程中双亲遗传算子计算效率较低;难以平衡不同进化时期种群中精英比例与种群多样性间、搜索深度与搜索广度间的关系等问题,本文设计一种混合遗传算法,在编解码方式上将配送网络信息分开表达,提高计算效率;在选择操作上引入平衡精英比例与种群多样性的控制参数;此外,还提出一种自适应搜索范围策略,以有效平衡搜索深度与搜索广度间的关系.通过实验例证和对比分析,验证了算法的有效性.研究成果为求解多中心联合配送车辆路径问题提供一种新思路,也可为相关的物流配送决策提供指导.
中图分类号:
范厚明,徐振林,李阳,刘文琪,耿静. 混合遗传算法求解多中心联合配送路径问题[J]. 上海交通大学学报, 2019, 53(8): 1000-1009.
FAN Houming,XU Zhenlin,LI Yang,LIU Wenqi,GENG Jing. Hybrid Genetic Algorithm for Solving Multi-Depot Joint Distribution Routing Problem[J]. Journal of Shanghai Jiaotong University, 2019, 53(8): 1000-1009.
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