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Active-guided evolution strategies for large-scale capacitated vehicle routing problems

机译:大规模制导车辆路径问题的主动制导进化策略

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We present an adaptation of the active-guided evolution strategies metaheuristic for the capacitated vehicle routing problem. The capacitated vehicle routing problem is a classical problem in operations research in which a set of minimum total cost routes must be determined for a fleet of identical capacitated vehicles in order to service a number of demand or supply points. The applied metaheuristic combines the strengths of the well-known guided local search and evolution strategies metaheuristics into an iterative two-stage procedure. The computational experiments were carried out on a set of 76 benchmark problems. The results demonstrate that the suggested method is highly competitive, providing the best-known solutions to 70 test instances.
机译:我们提出了针对能力受限的车辆路径问题的主动引导进化策略的变通方法。容量限制的车辆路线问题是运筹学中的经典问题,在该研究中,必须为一组相同容量的车辆确定最小总成本路线,以服务多个需求点或供应点。应用的元启发式方法将著名的本地指导搜索和进化策略元启发式方法的优势组合成一个迭代的两阶段过程。在一组76个基准问题上进行了计算实验。结果表明,所建议的方法具有很高的竞争力,可以为70个测试实例提供最著名的解决方案。

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