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Convergence and diversity evaluation for vector evaluated particle swarm optimization

Multi-objective optimization can be commonly found in many real world problems. In computational intelligence, Particle Swarm Optimization (PSO) algorithm has increasing popularity in solving optimization problems. An extended PSO algorithm called Vector Evaluated Particle Swarm Optimization (VEPSO)...

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Main Authors:	Sheng, L. K., Ibrahim, Z., Buyamin, S., Ahmad, A., Ibrahim, I., Jusof, M. F. M., Naim, F., Tumari, M. Z. M., Ghazali, K. H.
Format:	Conference or Workshop Item
Published:	2013
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/50964/ http://ieeexplore.ieee.org/document/6642213/
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id	my.utm.50964
record_format	eprints
spelling	my.utm.509642017-09-14T11:02:32Z http://eprints.utm.my/id/eprint/50964/ Convergence and diversity evaluation for vector evaluated particle swarm optimization Sheng, L. K. Ibrahim, Z. Buyamin, S. Ahmad, A. Ibrahim, I. Jusof, M. F. M. Naim, F. Tumari, M. Z. M. Ghazali, K. H. TK Electrical engineering. Electronics Nuclear engineering Multi-objective optimization can be commonly found in many real world problems. In computational intelligence, Particle Swarm Optimization (PSO) algorithm has increasing popularity in solving optimization problems. An extended PSO algorithm called Vector Evaluated Particle Swarm Optimization (VEPSO) has been introduced to solve multi-objective optimization problems. However, VEPSO quantitative performance measure has not been investigated. Hence, in this study, the performance of VEPSO algorithm is investigated by measuring the convergence and diversity by using standard test functions. In addition, comparisons with other optimization algorithms are also conducted. The results show that the VEPSO algorithm performs weakly in solving problems with concave, mixed, and disconnected Pareto frontier and performs badly in solving multi-modal problems. 2013 Conference or Workshop Item PeerReviewed Sheng, L. K. and Ibrahim, Z. and Buyamin, S. and Ahmad, A. and Ibrahim, I. and Jusof, M. F. M. and Naim, F. and Tumari, M. Z. M. and Ghazali, K. H. (2013) Convergence and diversity evaluation for vector evaluated particle swarm optimization. In: 2013 Proceedings of International Conference on Modelling, Identification and Control, ICMIC 2013. http://ieeexplore.ieee.org/document/6642213/
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/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Sheng, L. K. Ibrahim, Z. Buyamin, S. Ahmad, A. Ibrahim, I. Jusof, M. F. M. Naim, F. Tumari, M. Z. M. Ghazali, K. H. Convergence and diversity evaluation for vector evaluated particle swarm optimization
description	Multi-objective optimization can be commonly found in many real world problems. In computational intelligence, Particle Swarm Optimization (PSO) algorithm has increasing popularity in solving optimization problems. An extended PSO algorithm called Vector Evaluated Particle Swarm Optimization (VEPSO) has been introduced to solve multi-objective optimization problems. However, VEPSO quantitative performance measure has not been investigated. Hence, in this study, the performance of VEPSO algorithm is investigated by measuring the convergence and diversity by using standard test functions. In addition, comparisons with other optimization algorithms are also conducted. The results show that the VEPSO algorithm performs weakly in solving problems with concave, mixed, and disconnected Pareto frontier and performs badly in solving multi-modal problems.
format	Conference or Workshop Item
author	Sheng, L. K. Ibrahim, Z. Buyamin, S. Ahmad, A. Ibrahim, I. Jusof, M. F. M. Naim, F. Tumari, M. Z. M. Ghazali, K. H.
author_facet	Sheng, L. K. Ibrahim, Z. Buyamin, S. Ahmad, A. Ibrahim, I. Jusof, M. F. M. Naim, F. Tumari, M. Z. M. Ghazali, K. H.
author_sort	Sheng, L. K.
title	Convergence and diversity evaluation for vector evaluated particle swarm optimization
title_short	Convergence and diversity evaluation for vector evaluated particle swarm optimization
title_full	Convergence and diversity evaluation for vector evaluated particle swarm optimization
title_fullStr	Convergence and diversity evaluation for vector evaluated particle swarm optimization
title_full_unstemmed	Convergence and diversity evaluation for vector evaluated particle swarm optimization
title_sort	convergence and diversity evaluation for vector evaluated particle swarm optimization
publishDate	2013
url	http://eprints.utm.my/id/eprint/50964/ http://ieeexplore.ieee.org/document/6642213/
_version_	1643652898596323328
score	13.211869

Convergence and diversity evaluation for vector evaluated particle swarm optimization

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