文章基本信息

标题：Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem
本地全文：下载
作者：Nosheen Qamar ; Nadeem Akhtar ; Irfan Younas 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2018
卷号：9
期号：2
DOI：10.14569/IJACSA.2018.090251
出版社：Science and Information Society (SAI)
摘要：The Evolutionary Computation has grown much in last few years. Inspired by biological evolution, this field is used to solve NP-hard optimization problems to come up with best solution. TSP is most popular and complex problem used to evaluate different algorithms. In this paper, we have conducted a comparative analysis between NSGA-II, NSGA-III, SPEA-2, MOEA/D and VEGA to find out which algorithm best suited for MOTSP problems. The results reveal that the MOEA/D performed better than other three algorithms in terms of more hypervolume, lower value of generational distance (GD), inverse generational distance (IGD) and adaptive epsilon. On the other hand, MOEA-D took more time than rest of the algorithms.
关键词：Evolutionary computation; algorithms; NSGA-II; NSGA-III; MOEA-D; comparative analysis