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Peer-Reviewed Academic JournalInternational Journal of Applied Methods in Electronics and Computers
ISSN: 3023-4409DOI Prefix: 10.58190/ijamec
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Pages: 47-52

Particle Swarm Optimization for Continuous Function Optimization Problems

Muhlis ÖZDEMIR
Publication DateOctober 1, 2017
Volume / IssueVol. 5, No. 3 (pp. 47-52)
subject

Abstract

In this paper, particle swarm optimization is proposed for finding the global minimum of continuous functions and experimented on benchmark test problems. Particle swarm optimization applied on 21 benchmark test functions, and its solutions are compared to those former proposed approaches: ant colony optimization, a heuristic random optimization, the discrete filled function algorithm, an adaptive random search, dynamic random search technique and random selection walk technique. The implementation of the PSO on several test problems are reported with satisfactory numerical results when compared to previously proposed heuristic techniques. PSO is proved to be successful approach to solve continuous optimization problems.
Keywords:continuous function optimizationglobal minimumheuristic techniquesparticle swarm optimization
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How to Cite This Article

M. Ö. (2017). Particle Swarm Optimization for Continuous Function Optimization Problems. International Journal of Applied Methods in Electronics and Computers, 47-52. https://doi.org/10.18100/ijamec.2017331879