用遗传算法求解燃料分配问题:一种旅行推销员问题的方法

Rosshairy Abd. Rahman, Nurul Ezatty Mokhtar, Ummu Latifah Bahrom
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引用次数: 0

摘要

汽油或燃料是人们日常使用的产品,需求量很大。因此,每天都要将汽油从产地运送到每个加油站。这种分配过程关系到管理层,因为他们必须在利润最大化的同时最小化成本。因此,本文旨在开发一个模型,能够确定在雪兰莪州的一家公司交付这些汽油的最短路径。使用旅行推销员问题(TSP)方法解决了该问题,其中使用Google Maps应用程序收集数据。采用遗传算法(GA)实现了最短的距离。并将遗传算法解与爬坡法进行了比较。结果表明,遗传算法产生了较好的解,可将距离缩短至23 km。这项研究的发现将有助于该公司降低在雪兰莪州分销精炼燃料的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SOLVING A FUEL DISTRIBUTION PROBLEM USING GENETIC ALGORITHM: A TRAVELING SALESMANPROBLEMAPPROACH
Petrol or fuel is the product that people use daily and have a high demand. Therefore, the delivery of petrol from origin to each petrol station is done daily. This distribution process concerns the management as they have to minimize the cost while maximizing the profit. Hence, this paper aims to develop a model that is able to determine the shortest path for delivery these petrol in one company in Selangor. The problem is solved using Traveling Salesman Problem (TSP) approach, where the data were collected using Google Maps application. The shortest distance was attained using Genetic Algorithm (GA) technique. The solution obtained from GA was then compared with Hill Climbing technique. The results shows that GA produces better solution and could cut the distance up to 23 km. The finding of this research would help the company to reduce the cost of distributing refined fuel around Selangor.
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