Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem

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.

Nosheen Qamar, Nadeem Akhtar and Irfan Younas. “Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem”. International Journal of Advanced Computer Science and Applications (IJACSA) 9.2 (2018). http://dx.doi.org/10.14569/IJACSA.2018.090251

@article{Qamar2018,
title = {Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090251},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090251},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {2},
author = {Nosheen Qamar and Nadeem Akhtar and Irfan Younas}
}