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Solving A Vehicle Routing Problem With Time Windows By A Decomposition Technique And A Genetic Algorithm

机译:用分解技术和遗传算法求解带时间窗的车辆路径问题

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The present study investigates the cost concerns of distribution centers and formulates a vehicle routing problem with time window constraints accordingly. Based on the embedded structure of the original problem, a decomposition technique is employed to decompose the original problems to a clustering problem (main problem) and a set of traveling salesman problems (sub-problems) with time window constraints. This decomposition not only reduces the problem size but also enable the use of simpler solution procedures. A genetic algorithm is developed to solve the clustering problem, while a simple heuristic algorithm is formulated to solve the set of traveling salesman problems. The solution of the original problem is obtained through iterative interactions between the main problem and the set of sub-problems. The performance of the proposed approach is compared with the well-known insertion method and a manual scheduling of a distribution center.
机译:本研究调查了配送中心的成本问题,并据此提出了具有时间窗约束的车辆路径问题。基于原始问题的嵌入结构,采用分解技术将原始问题分解为聚类问题(主要问题)和一组具有时间窗约束的旅行商问题(子问题)。这种分解不仅可以减小问题的大小,而且可以使用更简单的解决方案。开发了一种遗传算法来解决聚类问题,同时制定了一种简单的启发式算法来解决旅行商问题。原始问题的解决方案是通过主要问题与子问题集之间的迭代交互来获得的。将该方法的性能与众所周知的插入方法和配送中心的手动调度进行了比较。

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