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Solving a Capacitated p-Median Location Allocation Problem Using Genetic Algorithm: A case study

机译:使用遗传算法解决电容p中位位置分配问题:一个案例研究

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Facility location-allocation problems have various applications in private and public sectors. A capacitated p-median problem is considered in this work which is computationally NPHard. The primary goal of this paper was to determine a set of p-facilities location in which all demand points are allocated and its average distance traveled from the customers' location to the selected p-facilities is minimized. In addition, the model also considered supplier's allocation for p facilities. A real world case study has been addressed, and genetic algorithm which consists of crossover and mutation operators was proposed in order to solve the problem. Computational results for different values of p were generated, and finally the optimum solution based on minimum cost was reported.
机译:设施位置分配问题在私人和公共部门拥有各种应用。 在这项工作中考虑了电容p中位问题,这是计算上的空中的。 本文的主要目标是确定一组P-acchility位置,其中分配了所有需求点,并且其从客户位置到所选P-angetion的平均距离被最小化。 此外,该模型还考虑供应商的P设施分配。 已经解决了一个真实的世界案例研究,提出了由交叉和突变运营商组成的遗传算法,以解决问题。 产生不同价值观的计算结果,最后报道了基于最低成本的最佳解决方案。

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