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Research Article | Open Access |

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) · Vol. 9, No. 2 · Published 2018 · Cited by 12

DOI: https://doi.org/10.14569/IJACSA.2018.090251

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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

How to Cite this Article

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). https://doi.org/10.14569/IJACSA.2018.090251

Qamar, Nosheen, et al.. "Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem." International Journal of Advanced Computer Science and Applications, vol. 9, no. 2, 2018, https://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},
  volume    = {9},
  number    = {2},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Nosheen Qamar and Nadeem Akhtar and Irfan Younas},
  doi       = {10.14569/IJACSA.2018.090251},
  url       = {https://doi.org/10.14569/IJACSA.2018.090251}
}

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