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A hybrid Genetic Algorithm for Vehicle Routing Problem with Time Windows

机译:有时间窗的车辆路径问题的混合遗传算法

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摘要

The Vehicle Routing Problem with Time Windows (VRPTW) consists of a homogenous set of vehicles and a set of customer located in a city. In VRPTW all the vehicles starts from the depot visit the customer and end at the depot. Each customer is visited exactly by one vehicle within the specified time window. The objective is to minimize the number of vehicles and total distance travelled simultaneously. This represents the multiobjective Vehicle Routing Problem with Time Windows. The proposed work consists of Hybrid Genetic Search with Diversity Control using the Genetic Algorithm for solving the VRPTW. The Pareto approach is used for finding the set of optimal solutions for achieving the multiobjective. The crossover operator is used for exchanging the best routes, which have shortest distance. Two mutation operators such as relocation mutation operator and split mutation operator were used in this application. In this, it accounts penalty for an infeasible solutions with respect to time-window and duration constrains. The computations are performed using the instances which are obtained from the VRPLIB.
机译:带时间窗的车辆路径问题(VRPTW)由一组同质的车辆和一组位于城市中的客户组成。在VRPTW中,所有车辆都从仓库出发,拜访客户并在仓库结束。在指定的时间范围内,一辆车正好会拜访每个客户。目的是最小化车辆数量和同时行驶的总距离。这代表了带有时间窗的多目标车辆路径问题。拟议的工作包括使用遗传算法解决VRPTW的具有多样性控制的混合遗传搜索。帕累托方法用于找到实现多目标的最优解集。交叉算子用于交换距离最短的最佳路线。在此应用程序中使用了两个突变算子,例如重定位突变算子和拆分突变算子。在这种情况下,它就时间窗和持续时间约束而言,提出了不可行的解决方案。使用从VRPLIB获得的实例执行计算。

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