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Particle swarm optimization

Particle swarm optimization Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. As researchers have learned about the technique, they have derived new versions, developed new applications, and published theoretical studies of the effects of the various parameters and aspects of the algorithm. This paper comprises a snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Swarm Intelligence Springer Journals

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References (128)

Publisher
Springer Journals
Copyright
Copyright © 2007 by Springer Science + Business Media, LLC
Subject
Computer Science; Computer Communication Networks ; Probability and Statistics in Computer Science; Computer Systems Organization and Communication Networks; Communications Engineering, Networks; Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)
ISSN
1935-3812
eISSN
1935-3820
DOI
10.1007/s11721-007-0002-0
Publisher site
See Article on Publisher Site

Abstract

Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. As researchers have learned about the technique, they have derived new versions, developed new applications, and published theoretical studies of the effects of the various parameters and aspects of the algorithm. This paper comprises a snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems.

Journal

Swarm IntelligenceSpringer Journals

Published: Aug 1, 2007

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