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：2237&2238
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
