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A hybrid metaheuristic for the time-dependent vehicle routing problem with hard time windows

机译:具有硬时间窗的时变车辆路径问题的混合元启发式算法

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摘要

This article paper presents a hybrid metaheuristic algorithm to solve the time-dependent vehicle routing problem with hard time windows. Time-dependent travel times are influenced by different congestion levels experienced throughout the day. Vehicle scheduling without consideration of congestion might lead to underestimation of travel times and consequently missed deliveries. The algorithm presented in this paper makes use of Large Neighbourhood Search approaches and Variable Neighbourhood Search techniques to guide the search. A first stage is specifically designed to reduce the number of vehicles required in a search space by the reduction of penalties generated by time-window violations with Large Neighbourhood Search procedures. A second stage minimises the travel distance and travel time in an ‘always feasible’search space. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%), travel distance (10.88%) and travel time (12.00%) compared to previous implementations in reasonable time
机译:本文提出了一种混合元启发式算法,用于解决带有硬时间窗的时变车辆路径问题。随时间变化的旅行时间受一天中不同拥堵程度的影响。在不考虑拥堵的情况下进行车辆调度可能会导致旅行时间估计不足,从而导致交付错过。本文提出的算法利用大邻域搜索方法和可变邻域搜索技术来指导搜索。第一阶段经过专门设计,通过减少大型邻居搜索程序对违反时间窗口所产生的罚款,来减少搜索空间中所需的车辆数量。第二阶段是在“始终可行”的搜索空间中最小化旅行距离和旅行时间。结果与可用测试实例的比较表明,与先前的实现方案相比,该算法能够在合理的时间内减少车辆数量(4.15%),行驶距离(10.88%)和行驶时间(12.00%)

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