A COMPARATIVE STUDY ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHMS FOR TRAVELING SALESMAN PROBLEMS

Authors:
Mehmet Cunkas;M. Yasin Ozsaglam
Affiliations:
Department of Electronics & Computer Education, Selcuk University, Konya, Turkey;Selcuk University, Bozkir Vocational High School, Bozkir, Konya, Turkey
Venue:
Cybernetics and Systems
Year:
2009

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Abstract

This article deals with a performance evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) for traveling salesman problem (TSP). This problem is known to be NP-hard, and consists of the solution containing N! permutations. The objective of the study is to compare the ability to solve the large-scale and other benchmark problems for both algorithms. All simulation has been performed using a software program developed in the Delphi environment. As yet, overall results show that genetic algorithms generally can find better solutions compared to the PSO algorithm, but in terms of average generation it is not good enough.