基于改进蚁群算法的带时间窗废品收集车辆路径问题

被引:2
作者
刘琼
刘秀城
张超勇
饶运清
机构
[1] 华中科技大学数字制造装备与技术国家重点实验室
基金
中央高校基本科研业务费专项资金资助;
关键词
大规模带时间窗车辆; 路径问题; 蚁群算法; 燃油消耗;
D O I
暂无
中图分类号
U492.22 []; TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
建立了以最小化燃油消耗为优化目标的带时间窗、司机休息时间以及多个中转处理中心的废品收集车辆路径问题模型。提出了一种改进最大最小蚁群算法,针对时间窗特点,设计了两类满足时间窗约束的动态候选列表以提高算法的搜索效率。在最大最小蚁群算法的概率状态转移规则中引入了带距离限制的最近邻域搜索。10个基准实例中的9个实例比当前文献的最优解更好,从而验证了该模型和算法的可行性和有效性。
引用
收藏
页码:247 / 254
页数:8
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