Route Determination Method to Minimize Distribution Cost and Total Time Balance by Using Multi-Objective Genetic Algorithm

Krismodianto, Santoso
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Abstract

. The subject of this research is a distribution company engaged in the distribution of eggs to many customers in Bandung. Distribution is carried out every day with 3 types of vehicles which are one way pick up, three ways pick up, and engkel truck. Based on preliminary research, the current route determination method is based on experience so the distance and travel time are thought could be improved. This affects the distribution costs that must be spent to distribute eggs to customers. Distributor also experience workload imbalance of vehicles that be used for the distribution process regarding to the travel time charged to each vehicle. The proposal in this study is used the metaheuristic method with the multi-objective genetic algorithm concerning to the multi-objective vehicle routing problem. This research is conducted during the fourth week of October 2018 and the chosen method is the proposed route determination method. The results of the comparison between the current system and the proposed system from this study obtained savings in terms of distribution costs of 18.03%, while in terms of total time balance, the distribution time range can be reduced to 95.52% so the workload of the vehicles are more balanced.
基于多目标遗传算法的配送成本和总时间平衡最小化的路线确定方法
. 本研究的对象是一家在万隆从事鸡蛋配送给众多客户的配送公司。每天有三种车辆进行配送,分别是单向提货、三路提货和英格尔卡车。在初步研究的基础上,现有的路线确定方法是基于经验的,认为距离和行驶时间可以改进。这影响了将鸡蛋分发给顾客的配送成本。经销商还会遇到车辆工作量不平衡的问题,这些车辆用于分配过程,涉及到每辆车收取的旅行时间。本研究采用多目标遗传算法的元启发式方法来研究多目标车辆路径问题。本研究于2018年10月第四周进行,选择的方法为建议的路线确定方法。通过对比本研究提出的系统与现有系统,配送成本节约18.03%,而在总时间平衡方面,配送时间范围可缩减至95.52%,使车辆的工作量更加平衡。
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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