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Article Information:
A Survey of the State of the Art in Particle Swarm Optimization
Mahdiyeh Eslami, Hussain Shareef, Mohammad Khajehzadeh and Azah Mohamed
Corresponding Author: Mahdiyeh Eslami
Submitted: January 11, 2012
Accepted: February 09, 2012
Published: May 01, 2012 |
Abstract:
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Meta-heuristic optimization algorithms have become popular choice for solving complex and
intricate problems which are otherwise difficult to solve by traditional methods. In the present study an attempt
is made to review the one main algorithm is a well known meta-heuristic; Particle Swarm Optimization (PSO).
PSO, in its present form, has been in existence for roughly a decade, a relatively short time compared with some
of the other natural computing paradigms such as artificial neural networks and evolutionary computation.
However, in that short period, PSO has gained widespread appeal amongst researchers and has been shown to
offer good performance in a variety of application domains, with potential for hybridization and specialization,
and demonstration of some interesting emergent behavior. This study comprises a snapshot of particle swarm
optimization from the authors’ perspective, including variations in the algorithm, modifications and refinements
introduced to prevent swarm stagnation and hybridization of PSO with other heuristic algorithms.
Key words: Hybridization, modification, particle swarm optimization, , , ,
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Cite this Reference:
Mahdiyeh Eslami, Hussain Shareef, Mohammad Khajehzadeh and Azah Mohamed, . A Survey of the State of the Art in Particle Swarm Optimization. Research Journal of Applied Sciences, Engineering and Technology, (09): 1181-1197.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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