绿色车辆路由优化基于动态约束选择共进化的算法
Lu-Jie Zhou1, Hai-Fei Zhang2, Jun-Hao Fu3,4
1School of Automobile and Transportation, Tianjin University of Technology and Education, Tianjin, 300222, China.
Scientific reports
|May 21, 2025
概括
本研究引入了绿色车辆路线的新模型,考虑实时流量和交付时间窗口. 开发的算法有效地降低了物流运营的成本和排放.
科学领域:
- 运营研究 运营研究
- 运输 运输 物流 后勤
- 环境可持续性 环境可持续性
背景情况:
- 现有的绿色车辆路线模型往往缺乏单一目标的解决方案,并且无法考虑实时速度变化.
- 变化速度和容量等动态因素对物流中的碳排放产生重大影响.
研究的目的:
- 建立一个多目标绿色车辆路由问题,在时间变化的条件下 (MOGVRPTW-TV) 设有时间窗口限制.
- 为解决MOGVRPTW-TV.TV提出一个基于共进化的框架的受约束的多目标进化算法.
主要方法:
- 开发了一个模型,包括时间变化的速度和容量变化影响碳排放.
- 提出了一种共同进化的算法,其中包括用于解决方案多样性的转移拥挤距离,以及用于优化动态约束选择策略.
主要成果:
- 该算法有效地避免了交通拥堵时期.
- 证明了总体分销成本的大幅降低.
- 实现了车辆更低的燃料消耗和碳排放.
结论:
- 拟议的MOGVRPTW-TV模型及其相关算法为复杂的物流挑战提供了有效的解决方案.
- 该方法平衡了融合和多样性,从而提高了绿色物流的效率和环境效益.
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