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DOI: 10.14569/IJACSA.2018.090251
PDF

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

Author 1: Nosheen Qamar
Author 2: Nadeem Akhtar
Author 3: Irfan Younas

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 2, 2018.

  • Abstract and Keywords
  • How to Cite this Article
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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.

Keywords: Evolutionary computation; algorithms; NSGA-II; NSGA-III; MOEA-D; comparative analysis

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}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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