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The application of the genetic algorithm to multi-criteria warehouses location problems on the logistics network

机译:遗传算法在物流网络多标准仓库选址问题中的应用

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This paper presents multi-criteria warehouses location problem in the logistics network. In order to solve this problem the location model was developed. The limitations and optimization criteria of the model were determined. Optimization criteria refer to transportation costs, costs associated with warehouses, e.g.: local taxes, expenditure on starting the warehouse, the constant costs, the labour force costs, the purchase costs of the additional land for the expansion, the transition costs of the raw material via the warehouses. The final location of warehouse facilities was obtained using a genetic algorithm. The genetic algorithm was developed in order to solve the multi-criteria warehouses location problem. This paper describes the stages of the genetic algorithm i.e. the stage of designating the initial population, the crossover and mutation process, the adaptation function. In this paper, the process of calibration of this algorithm was presented. The results of the genetic algorithm were compared with the random results.
机译:本文提出了物流网络中多标准仓库的选址问题。为了解决这个问题,开发了位置模型。确定了模型的局限性和优化标准。优化标准涉及运输成本,与仓库相关的成本,例如:地方税,启动仓库的支出,固定成本,劳动力成本,扩建用地的购置成本,原材料的过渡成本通过仓库。使用遗传算法获得仓库设施的最终位置。为了解决多标准仓库的选址问题,开发了遗传算法。本文介绍了遗传算法的各个阶段,即指定初始种群的阶段,交叉和变异过程,适应函数。本文提出了该算法的标定过程。将遗传算法的结果与随机结果进行比较。

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