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Particle Swarm Optimization: Technique, System and Challenges

by Dian Palupi Rini, Siti Mariyam Shamsuddin, Siti Sophiyati Yuhaniz
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 14 - Number 1
Year of Publication: 2011
Authors: Dian Palupi Rini, Siti Mariyam Shamsuddin, Siti Sophiyati Yuhaniz
10.5120/1810-2331

Dian Palupi Rini, Siti Mariyam Shamsuddin, Siti Sophiyati Yuhaniz . Particle Swarm Optimization: Technique, System and Challenges. International Journal of Computer Applications. 14, 1 ( January 2011), 19-27. DOI=10.5120/1810-2331

@article{ 10.5120/1810-2331,
author = { Dian Palupi Rini, Siti Mariyam Shamsuddin, Siti Sophiyati Yuhaniz },
title = { Particle Swarm Optimization: Technique, System and Challenges },
journal = { International Journal of Computer Applications },
issue_date = { January 2011 },
volume = { 14 },
number = { 1 },
month = { January },
year = { 2011 },
issn = { 0975-8887 },
pages = { 19-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume14/number1/1810-2331/ },
doi = { 10.5120/1810-2331 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:02:19.886002+05:30
%A Dian Palupi Rini
%A Siti Mariyam Shamsuddin
%A Siti Sophiyati Yuhaniz
%T Particle Swarm Optimization: Technique, System and Challenges
%J International Journal of Computer Applications
%@ 0975-8887
%V 14
%N 1
%P 19-27
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other hand, basic PSO is more appropriate to process static, simple optimization problem. Modification PSO is developed for solving the basic PSO problem. The observation and review 46 related studies in the period between 2002 and 2010 focusing on function of PSO, advantages and disadvantages of PSO, the basic variant of PSO, Modification of PSO and applications that have implemented using PSO. The application can show which one the modified or variant PSO that haven’t been made and which one the modified or variant PSO that will be developed.

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Index Terms

Computer Science
Information Sciences

Keywords

Particle Swarm Optimization (PSO) Variant PSO Modification PSO Basic PSO problem Bird Flocking Evolutionary Optimization biologically inspired computational search

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