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A Hybrid Approach Based on Ant Colony System for the VRPTW

机译:基于蚁群系统的VRPTW混合方法

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The main objective of vehicle routing problem (VRP) is to minimize the total required fleet size for serving all customers. Secondary objectives are to minimize the total distance traveled or to minimize the total route duration of all vehicles. In this paper, we present a hybrid ant colony System, named IACS, coupled with the iterated local search (ILS) algorithm for the VRP with time windows (VRPTW). The ILS can help to escape local optimum. Experiments on various aspects of the algorithm and computational results for some benchmark problems are reported. We compare our approach with some classic, powerful meta-heuristics and show that the proposed approach can obtain the better quality of the solutions.
机译:车辆路径问题(VRP)的主要目标是最大程度地减少服务所有客户所需的总车队规模。第二个目标是使所有车辆的总行驶距离最小化或使总路线持续时间最小化。在本文中,我们提出了一个名为IACS的混合蚁群系统,并结合了带有时间窗(VRPTW)的VRP的迭代局部搜索(ILS)算法。 ILS可以帮助避免局部最优。报告了算法各方面的实验以及一些基准问题的计算结果。我们将我们的方法与一些经典的,强大的元启发式方法进行了比较,并表明所提出的方法可以获得更好的解决方案质量。

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