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Stochastic p-hub center covering problem with delivery time constraint

机译:具有交货时间约束的随机p-hub中心覆盖问题

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In this paper, stochastic version of p-hub covering center problem (we call it Sp-HCCP) has been presented that optimizes the location of the hubs and allocation of non-hub nodes to hub nodes. The goal of our model is to maximize the minimum service-level that can achieved for a given maximum path length (delivery time on the path). We have formulated this problem using the chance constraints with a linear structure and a Genetic Algorithm (GA) has been developed to solve large scale problems. Numerical examples are solved by GA and the results are compared with exact solutions to prove the efficiency and robustness of the proposed GA. The results show that the optimal solutions are sensitive to the amount of stochastic demands also they show the precision of proposed GA method.
机译:在本文中,提出了p-hub覆盖中心问题(我们称为Sp-HCCP)的随机版本,该版本优化了集线器的位置以及将非集线器节点分配给集线器节点的过程。我们模型的目标是最大化给定最大路径长度(路径上的交付时间)可以达到的最小服务级别。我们使用具有线性结构的机会约束来公式化此问题,并且已经开发了遗传算法(GA)来解决大规模问题。遗传算法求解了数值实例,并将结果与​​精确解进行了比较,以证明所提出遗传算法的效率和鲁棒性。结果表明,最优解对随机需求量敏感,也表明了所提出遗传算法的精度。

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