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The particle swarm - explosion, stability, and convergence in a multidimensional complex space

Clerc, M., Kennedy, J.·2002·IEEE Transactions on Evolutionary Computation

Abstract

The particle swarm is an algorithm for finding optimal regions of complex search spaces through the interaction of individuals in a population of particles. This paper analyzes a particle's trajectory as it moves in discrete time (the algebraic view), then progresses to the view of it in continuous time (the analytical view). A five-dimensional depiction is developed, which describes the system completely. These analyses lead to a generalized model of the algorithm, containing a set of coefficients to control the system's convergence tendencies. Some results of the particle swarm optimizer, implementing modifications derived from the analysis, suggest methods for altering the original algorithm in ways that eliminate problems and increase the ability of the particle swarm to find optima of some well-studied test functions.

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Metadata

Authors
Clerc, M., & Kennedy, J.
Venue
IEEE Transactions on Evolutionary Computation
Published
2002
Volume
6
Issue
1
Pages
58-73
ISSN
1089-778X (ISSN-L)
OpenAlex
W2169245194
Cited by
9,017
References
0
FWCI
85.65
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The particle swarm - explosion, stability, and convergence in a multidimensional complex space. https://app.cochat.ai/papers/10.1109/4235.985692
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Clerc, M., & Kennedy, J. (2002). The particle swarm - explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation. https://doi.org/10.1109/4235.985692

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.