文章基本信息

标题：Increasing the Performance of Genetic Algorithm by Using Different Selection: Vehicle Routing Problem Cases
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作者：Ismail Yusuf Panessai ; Muhammad Modi bin Lakulu ; Siva Kumar A/L Subramaniam 等
期刊名称：Lecture Notes in Engineering and Computer Science
印刷版ISSN：2078-0958
电子版ISSN：2078-0966
出版年度：2018
卷号：2231&2232
页码：117-122
出版社：Newswood and International Association of Engineers
摘要：This research was focused on a heterogeneous fleet of passenger ships multi-depot by using the genetic algorithm (GA) to solve a combinatorial problem i.e. vehicle routing problem (VRP). The objective of this study is to compare the roulette wheel selection, single cut point crossover, and shift neighborhood mutation with selection based on selection rate, single cut point crossover, and shift neighborhood mutation to minimize the sum of the fuel consumption travelled, the cost for violations of the ship draft and sea depth, and penalty cost for violations of the load factor; to maximize the number port of call; and to maximize load factor. Problem-solving in this study is how to generate feasible route combinations for rich VRP that meets all the requirements with the optimum solution. Route generated by roulette wheel selection, single cut point crossover, and shift neighborhood mutation could decrease fuel consumption about 17.8990% compared to selection rate, single cut point crossover, and shift neighborhood mutation about 18.8825%.
关键词：Vehicle Routing Problem; Genetic Algorithms; Multi;Depot; Roulette wheel selection; Rank & selection based on selection Rate