基于混合算法的带时间窗车辆路径问题

Hybrid metaheuristics for the vehicle routing problem with time windows

使用改进蚁群算法结合大规模邻域搜索算法解决带时窗限制的车辆路径问题.首先对蚁群算法信息素及算法结构进行分析及改进,并提出了新的解题策略,由此得到可行解;然后在区域改善部分用邻域搜索算法进一步提高解的性能.给出混合算法计算Solomon100国际标准题库问题的结果,并与同类方法的文献最优解进行比较.

A hybrid algorithm based on a modified ant colony optimization algorithm （ACO） and large neighborhood search （LNS） is proposed to solve a delivery vehicle routing problem with time window constraints （VRPTW）. Firstly, an ant colony system is analyzed primarily. A new improved method of the traditional operation is then presented. This new ant colony optimization is used to get the initial solution of the vehicle routing problems with time window. In the local search improvement phase, large neighborhood search modules are also proposed to improve the result. Finally, Solomon＇s benchmark instances （VRPTW 100-customer） are tested for the algorithm and compared to the best solutions found in the literature.