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Solving Multiple Depot Vehicle Routing Problem (MDVRP) using Genetic Algorithm

机译：用遗传算法求解多车场车辆路径问题（MDVRP）

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摘要

Vehicle Routing Problem is a NP-Hard classical complex combinatorial problem described as task of determining efficient and shortest delivery or pickup routes to service several customers scattered in different geographical regions with a fleet of vehicles with additional predefined constraints to satisfy real-life scenarios. Vehicle Routing Problem has wide applications in Logistics and Transportation with growing economic importance. In Solutions of Vehicle Routing Problem maintaining the defined restrictions is of high Interest. Exact solutions of Vehicle Routing Problem can't be obtained due requirement of high computation time. Due to Genetic Algorithm's stochastic characteristics and efficiency in solving combinatorial problems it is used to find true and approximate solutions of Vehicle Routing Problem. For constrained variants of Vehicle Routing Problem feasible space is smaller than whole search space and Genetic Algorithm finds a solution with high precision that doesn't violate any of the constraints.
机译：车辆路线问题是NP-Hard的经典复杂组合问题，描述为确定有效和最短交付或接送路线的任务，以服务散布在不同地理区域中的多个客户，这些车辆具有附加的预定义约束来满足实际场景。车辆路径问题在物流和运输中具有广泛的经济意义。在车辆路径问题的解决方案中，保持定义的限制非常重要。由于需要大量的计算时间，所以无法获得车辆路径问题的精确解。由于遗传算法的随机性和求解组合问题的效率，它被用来寻找车辆路径问题的真实和近似解。对于车辆路径问题的约束变体，可行空间小于整个搜索空间，并且遗传算法找到了不违反任何约束条件的高精度解决方案。

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