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Vehicle Routing Problem in Pharmaceuticals Distribution and Genetic Algorithm Application

机译:药品配送中的车辆路径问题及其遗传算法的应用

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Since vehicle routing problem was first expressed in mathematical terms in late 1950s, it has found ways of application for many daily problems in different disciplines (waste collection, product transportation from warehouses to supermarkets, school buses etc.) as well as being one of the most academically researched subjects. Apart from small scale problems, vehicle routing problem becomes np-hard combinatorial optimization problem especially when trying to solve real daily life problems. Therefore, although heuristic algorithms do not guarantee optimum results, they are used quite often in vehicle routing problems.In this study, the routing problem of a main pharmaceuticals warehouse for delivering orders to 200 pharmacies operating in three different cities and their districts is solved using genetic algorithm, one of the most effective and most used heuristic algorithms. The model devised in the study determines distribution route from the main warehouse to pharmacies with minimum cost by minimizing total travel distance and number of vehicles and using vehicle capacities in the most effective way possible. In the end, two optimum solutions with regards to various aspects such as total distance and number of vehicles are presented with their cost values.
机译:自1950年代末首次以数学术语表达车辆路线问题以来,它已经找到了解决不同学科中许多日常问题(废物收集,从仓库到超市的产品运输,校车等)的方法,并且是其中的一种。大多数学术研究的科目。除小规模问题外,车辆路线选择问题也成为np-hard组合优化问题,尤其是在尝试解决实际日常生活问题时。因此,尽管启发式算法不能保证获得最佳结果,但它们经常用于车辆路线选择问题中。本研究使用以下方法解决了主要药品仓库的路线选择问题,该问题是通过向三个不同城市和地区运营的200家药店交付订单来解决的遗传算法,最有效和最常用的启发式算法之一。该研究中设计的模型通过最小化总行驶距离和车辆数量,并以最有效的方式利用车辆容量,以最小的成本确定了从主仓库到药房的分销路线。最后,针对各个方面(例如总距离和车辆数量)提出了两个最佳解决方案及其成本值。

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