Solving the distribution and transportation of multi-depot vehicle routing problem based on Genetic Algorithms

Roxana Flores-Quispe, Yuber Velazco-Paredes
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Abstract

In the last years the genetic algorithm (GA) has demonstrated great interest for many researchers to resolve analysis and optimization problems, this algorithm is inspired from the natural selection and uses the concept of survival of fittest, for that reason in this study the genetic algorithms is applied to optimize of the distribution and transportation of multidepots vehicles routing. This proposed system includes two stages. In the first stage an model of GA has been proposed to resolve the distribution problem and in the second stage other model of GA has been designed to find the optimal sequence of deliveries that must cover each company vehicle during its route. This method has been compared against Ant Colony Algorithm and shows a improvement in terms of effectiveness.
基于遗传算法的多车场车辆分配与运输路线问题的求解
近年来,遗传算法(GA)在解决分析和优化问题方面引起了许多研究人员的极大兴趣,该算法的灵感来自自然选择,并采用了适者生存的概念,因此本研究将遗传算法应用于多库车辆分配和运输路线的优化。该系统包括两个阶段。在第一阶段,提出了一个遗传算法模型来解决配送问题,在第二阶段,设计了另一个遗传算法模型来寻找必须覆盖公司每辆车在其路线上的最优配送顺序。将该方法与蚁群算法进行了比较,结果表明,该方法的有效性有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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