印尼首都楠榜的PT. Pos (PT. Pos)项目的基因算法优化旅行销售员

Saiful Rohman, L. Zakaria, Asmiati Asmiati, Aang Nuryaman
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引用次数: 4

摘要

优化是一个过程,以获得最小或最大值的函数,机会。其中一个涉及优化过程的问题是旅行商问题(TSP)。本研究中讨论的TSP案例研究与PT. Pos Indonesia在班达楠榜市进行的货物配送问题有关。其中一些问题包括货物交付延迟、邮局服务满意度下降、复杂货物的配送路线等。PT. Pos Indonesia利用TSP概念解决所遇到的问题,可以通过遗传算法的方法来解决(搜索算法基于自然选择机制和生物进化)。使用遗传算法方法解决所讨论的问题,结果表明,要使用顺序交叉和反转突变实现测试过程的最优位置,需要从10次重试尝试(80%)中重复该过程8次。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimisasi Travelling Salesman Problem dengan Algoritma Genetika pada Kasus Pendistribusian Barang PT. Pos Indonesia di Kota Bandar Lampung
Optimization is the process to get the minimum or maximum value of a function, opportunity. One of the problems involving the optimization process is Travelling Salesman Problem (TSP). The TSP case study discussed in this research is related to the problem of distribution of goods conducted by PT. Pos Indonesia in Bandar Lampung city. Some of the issues in question include delays in delivery of goods, less satisfaction in post Office services, a route to distribute complex goods and others. The resolution of the problem encountered by PT. Pos Indonesia by using the TSP concept in question can be solved by method of genetic algorithm (the search algorithm is based on natural selection mechanism and biological evolution). The use of the genetic algorithm method in resolving the problems discussed gives results that to achieve the optimal position of the testing process using the order crossover and inversion mutation need to be done repeating the process 8 times from 10 retry attempts (80%).
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