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An overview of particle swarm optimization variants

Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis.

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Bibliographic Details
Main Authors: Muhammad Imran, Rathiah, Hashim, Noor Elaiza, Abd Khalid
Other Authors: radhiah@uthm.edu.my
Format: Working Paper
Language:English
Published: Malaysian Technical Universities Network (MTUN) 2013
Subjects:
Particle swarm optimization (PSO)
PSO variants
Overview of PSO
PSO and mutation operators
PSO and inertia weight
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/30676
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spelling my.unimap-306762013-12-20T03:46:22Z An overview of particle swarm optimization variants Muhammad Imran Rathiah, Hashim Noor Elaiza, Abd Khalid radhiah@uthm.edu.my elaiza@tmsk.uitm.edu.my Particle swarm optimization (PSO) PSO variants Overview of PSO PSO and mutation operators PSO and inertia weight Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis. Particle swarm optimization (PSO) is a stochastic algorithm used for the optimization problems proposed by Kennedy [1] in 1995. It is a very good technique for the optimization problems. But still there is a drawback in the PSO is that it stuck in the local minima. To improve the performance of PSO, the researchers proposed the different variants of PSO. Some researchers try to improve it by improving initialization of the swarm. Some of them introduce the new parameters like constriction coefficient and inertia weight. Some researchers define the different method of inertia weight to improve the performance of PSO. Some researchers work on the global and local best particles by introducing the mutation operators in the PSO. In this paper, we will see the different variants of PSO with respect to initialization, inertia weight and mutation operators. 2013-12-20T03:46:22Z 2013-12-20T03:46:22Z 2012-11-20 Working Paper p. 583-587 http://hdl.handle.net/123456789/30676 en Proceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012; Malaysian Technical Universities Network (MTUN)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Particle swarm optimization (PSO)
PSO variants
Overview of PSO
PSO and mutation operators
PSO and inertia weight
spellingShingle Particle swarm optimization (PSO)
PSO variants
Overview of PSO
PSO and mutation operators
PSO and inertia weight
Muhammad Imran
Rathiah, Hashim
Noor Elaiza, Abd Khalid
An overview of particle swarm optimization variants
description Malaysian Technical Universities Conference on Engineering and Technology (MUCET) 2012 organised by technical universities under the Malaysian Technical Universities Network (MTUN), 20th - 21st November 2012 at Hotel Seri Malaysia, Kangar, Perlis.
author2 radhiah@uthm.edu.my
author_facet radhiah@uthm.edu.my
Muhammad Imran
Rathiah, Hashim
Noor Elaiza, Abd Khalid
format Working Paper
author Muhammad Imran
Rathiah, Hashim
Noor Elaiza, Abd Khalid
author_sort Muhammad Imran
title An overview of particle swarm optimization variants
title_short An overview of particle swarm optimization variants
title_full An overview of particle swarm optimization variants
title_fullStr An overview of particle swarm optimization variants
title_full_unstemmed An overview of particle swarm optimization variants
title_sort overview of particle swarm optimization variants
publisher Malaysian Technical Universities Network (MTUN)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/30676
_version_ 1643795564983222272
score 13.214268

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