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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem
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An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

机译:枢纽定位路径问题的内共生进化算法

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We consider a capacitated hub location-routing problem (HLRP) which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitatedp-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA) which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.
机译:我们考虑了一个受限制的枢纽位置路由问题(HLRP),该问题结合了枢纽位置问题和多枢纽车辆路由决策。 HLRP不仅确定了capacitatedp-hub在一组潜在枢纽中的位置,而且还处理了车辆的路线,以满足客户的需求。该问题被公式化为0-1混合整数规划模型,其目标是最小的总成本包括路由成本,固定集线器成本和固定车辆成本。由于HLRP对大型问题的要求不切实际,因此我们开发了一种基于共生共生进化算法(EEA)的解决方法,该方法可同时解决轮毂位置和车辆路径问题。通过比较研究检查了所提出算法的性能。实验结果表明,提出的EEA可以作为供应链网络规划的可行解决方案。

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