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

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...

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Main Author: SENTHIL ARUMUGAM, M.
Format: Article
Published: 2006
Subjects:
Online Access:http://shdl.mmu.edu.my/2005/
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author SENTHIL ARUMUGAM, M.
author_facet SENTHIL ARUMUGAM, M.
author_sort SENTHIL ARUMUGAM, M.
building MMU Institutional Repository
collection Online Access
description 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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spelling mmu-20052011-08-10T07:40:28Z http://shdl.mmu.edu.my/2005/ ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS SENTHIL ARUMUGAM, M. TA Engineering (General). Civil engineering (General) 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. 2006-03 Article PeerReviewed SENTHIL ARUMUGAM, M. (2006) ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS. International Journal of Computational Methods, 3 (1). pp. 97-114. ISSN 02198762 http://dx.doi.org/10.1142/S0219876206000862 doi:10.1142/S0219876206000862 doi:10.1142/S0219876206000862
spellingShingle TA Engineering (General). Civil engineering (General)
SENTHIL ARUMUGAM, M.
ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS
title ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS
title_full ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS
title_fullStr ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS
title_full_unstemmed ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS
title_short ON THE ANALYSIS OF THE PERFORMANCES OF PARTICLE SWARM OPTIMIZATION ALGORITHM WITH GLOBALLY AND LOCALLY TUNED INERTIA WEIGHT VARIANTS
title_sort on the analysis of the performances of particle swarm optimization algorithm with globally and locally tuned inertia weight variants
topic TA Engineering (General). Civil engineering (General)
url http://shdl.mmu.edu.my/2005/
http://shdl.mmu.edu.my/2005/
http://shdl.mmu.edu.my/2005/