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Improving vector evaluated particle swarm optimisation using multiple nondominated leaders

The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the...

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Main Authors: Lim, Kian Sheng, Bunyamin, Salinda, Ahmad, Anita, Shapiai, Mohd. Ibrahim, Naim, Faradila, Mubin, Marizan, Kim, Donghwa
Format: Article
Language:English
Published: The Scientific World Journal 2014
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/53126/1/SalindaBuyamin2014_ImprovingVectorEvaluatedParticleSwarmOptimisation.pdf
http://eprints.utm.my/id/eprint/53126/
http://dx.doi.org/10.1155/2014/364179
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id my.utm.53126
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spelling my.utm.531262018-07-19T07:25:11Z http://eprints.utm.my/id/eprint/53126/ Improving vector evaluated particle swarm optimisation using multiple nondominated leaders Lim, Kian Sheng Bunyamin, Salinda Ahmad, Anita Shapiai, Mohd. Ibrahim Naim, Faradila Mubin, Marizan Kim, Donghwa TK Electrical engineering. Electronics Nuclear engineering The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept of multiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume. The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms. The Scientific World Journal 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/53126/1/SalindaBuyamin2014_ImprovingVectorEvaluatedParticleSwarmOptimisation.pdf Lim, Kian Sheng and Bunyamin, Salinda and Ahmad, Anita and Shapiai, Mohd. Ibrahim and Naim, Faradila and Mubin, Marizan and Kim, Donghwa (2014) Improving vector evaluated particle swarm optimisation using multiple nondominated leaders. Scientific World Journal . ISSN 1537-744X http://dx.doi.org/10.1155/2014/364179 DOI: 10.1155/2014/364179
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Lim, Kian Sheng
Bunyamin, Salinda
Ahmad, Anita
Shapiai, Mohd. Ibrahim
Naim, Faradila
Mubin, Marizan
Kim, Donghwa
Improving vector evaluated particle swarm optimisation using multiple nondominated leaders
description The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept of multiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume. The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms.
format Article
author Lim, Kian Sheng
Bunyamin, Salinda
Ahmad, Anita
Shapiai, Mohd. Ibrahim
Naim, Faradila
Mubin, Marizan
Kim, Donghwa
author_facet Lim, Kian Sheng
Bunyamin, Salinda
Ahmad, Anita
Shapiai, Mohd. Ibrahim
Naim, Faradila
Mubin, Marizan
Kim, Donghwa
author_sort Lim, Kian Sheng
title Improving vector evaluated particle swarm optimisation using multiple nondominated leaders
title_short Improving vector evaluated particle swarm optimisation using multiple nondominated leaders
title_full Improving vector evaluated particle swarm optimisation using multiple nondominated leaders
title_fullStr Improving vector evaluated particle swarm optimisation using multiple nondominated leaders
title_full_unstemmed Improving vector evaluated particle swarm optimisation using multiple nondominated leaders
title_sort improving vector evaluated particle swarm optimisation using multiple nondominated leaders
publisher The Scientific World Journal
publishDate 2014
url http://eprints.utm.my/id/eprint/53126/1/SalindaBuyamin2014_ImprovingVectorEvaluatedParticleSwarmOptimisation.pdf
http://eprints.utm.my/id/eprint/53126/
http://dx.doi.org/10.1155/2014/364179
_version_ 1643653302975463424
score 13.211869

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