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Hybrid Genetic Algorithm for Vehicle Routing Problem with Time Windows

机译:带时间窗的车辆路径问题的混合遗传算法

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Abstract-Vehicle Routing Problem (VRP) is an important class of scheduling optimization problems in the supply chain management. Vehicle Routing Problem with Time Windows (VRPTW) is an extension of VRP and involves the setoff of a fleet of vehicles from a depot to serve a number of customers at different geographic locations for within specific time windows before returning to the depot eventually. This study aims to solve VRPTW, which has received considerable attention in recent years. To solve this problem, this study suggests a hybrid genetic algorithm combined with priority rule heuristic to make an initial population and interchange mechanism to increase the diversity of the population and enhance the local search, applying guiding mutation to find improved descendant and using the Bi-directional Decoding (BDD) to find the better solution of the same chromosome. Finally, the repairing method is applied to reduce the number of non-feasible solutions in population. Experimental results show that the proposed hybrid algorithm has a better performance than other related algorithms.
机译:抽象车辆路径问题(VRP)是供应链管理中一类重要的调度优化问题。带时间窗的车辆路径问题(VRPTW)是VRP的扩展,涉及从车场出发的一批车队在特定的时间窗内为不同地理位置的多个客户提供服务,然后最终返回车场。这项研究旨在解决VRPTW,VRPTW近年来受到了广泛的关注。为了解决这个问题,本研究提出了一种混合遗传算法,结合优先级规则启发式算法,以建立初始种群和交换机制,以增加种群的多样性并增强局部搜索,应用引导突变来寻找改良的后代,并使用Bi-定向解码(BDD),以找到相同染色体的更好解决方案。最后,采用修复方法来减少人口中不可行解决方案的数量。实验结果表明,提出的混合算法具有比其他相关算法更好的性能。

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