oaioai:shdl.mmu.edu.my:2005

ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS

Abstract

The investigation of the performance of Particle Swarm Optimization (PSO) algorithm with the new variants to inertia weight in computing the optimal control of a single stage hybrid system is presented in this paper. Three new variants for inertia weight are defined and their applicability with the PSO algorithm is thoroughly explained. The results obtained through the new proposed methods are compared with the existing PSO algorithm, which has a time varying inertia weight from a higher value to a lower value. The proposed methods provide both faster convergence and optimal solution with better accuracy

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oaioai:shdl.mmu.edu.my:2005Last time updated on 10/28/2013

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