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Adaptive particle swarm optimization

Authors: Keiichiro Yasuda; Azuma Ide; Nobuhiro Iwasaki;

Adaptive particle swarm optimization

Abstract

The particle swarm optimization (PSO) method is one of the most powerful methods for solving unconstrained and constrained global optimization problems. Little is, however, known about how the PSO method works or finds a globally optimal solution of a global optimization problem when the method is applied to global optimization problems. This paper deals with the analysis of the dynamics of PSO in order to obtain an understanding about how it searches a globally optimal solution and a strategy about how to tune its parameters. While a generalized reduced model of PSO is proposed in order to analyze the dynamics of PSO, the stability analysis is carried out on the basis of both the eigenvalue analysis and some numerical simulations on a typical global optimization problem.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
49
Top 10%
Top 1%
Top 10%
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