Comparative analysis of evolutionary algorithms for multi-objective Travelling Salesman Problem

9Citations
Citations of this article
18Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Qamar, N., Akhtar, N., & Younas, I. (2018). Comparative analysis of evolutionary algorithms for multi-objective Travelling Salesman Problem. International Journal of Advanced Computer Science and Applications, 9(2), 374–379. https://doi.org/10.14569/IJACSA.2018.090251

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free