Optimization of a spare parts distribution system using a genetic algorithm

Alena Rybičková, D. Mocková, Adela Karaskova, Jakub Brodský
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引用次数: 1

Abstract

In this paper we focus on the system of the spare parts distribution for authorised garages in the Czech republic and its optimization based on genetic algorithm. Real world problem of garages supply consists of the design of the optimal location of distribution depots and the design of routes that are used for everyday delivery of spare parts. Both of these sub-problems that belong to NP-hard problems are solved separately using genetic algorithm. In the facility location problem, the set of customers, set of potential locations of facilities and distances for all their combinations are given and our goal is to select location of facilities with the minimum costs based on chosen criterion. In the second part of the optimization the vehicle routing problem is solved where the goal is to determine the routes described as a sequence of customers visited on this route. Every route starts and ends in the depot and is limited by capacity of the vehicle. Homogeneous fleet was used in this problem.
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基于遗传算法的备件配送系统优化
本文研究了捷克授权汽车修理厂备件配送系统及其基于遗传算法的优化问题。现实生活中的车库供应问题包括分配仓库的最优位置设计和日常备件配送路线的设计。这两个属于np困难问题的子问题分别用遗传算法求解。在设施选址问题中,给定了一组客户、一组潜在的设施选址和它们所有组合的距离,我们的目标是根据所选标准选择成本最小的设施选址。在优化的第二部分,解决了车辆路线问题,其目标是确定在此路线上访问的客户序列所描述的路线。每条路线的起点和终点都在仓库,并受到车辆容量的限制。该问题采用同构舰队。
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