Particle Swarm Optimization for Continuous Function Optimization Problems


ÖZDEMİR M.

INTERNATİONAL JOURNAL OF APPLİED MATHEMATİCS, ELECTRONİCS AND COMPUTERS, vol.5, pp.47-52, 2017 (Peer-Reviewed Journal)

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 is reported with satisfactory numerical results when compared to previously proposed heuristic techniques. PSO is proved to be successful approach to solve continuous optimization problems.