Analyzing Convergence and Rates of Convergence of Particle Swarm Optimization Algorithms Using Stochastic Approximation Methods

Recently, much progress has been made on particle swarm optimization (PSO). A number of works have been devoted to analyzing the convergence of the underlying algorithms. Nevertheless, in most cases, rather simplified hypotheses are used. For example, it often assumes that the swarm has only one par...

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Veröffentlicht in:	IEEE transactions on automatic control Jg. 60; H. 7; S. 1760 - 1773
Hauptverfasser:	Quan Yuan, Yin, George
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2015 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Approximation algorithms Approximation methods Convergence Optimization Particle swarm optimization Queuing theory rate of convergence stochastic approximation Stochastic processes weak convergence rate of convergence stochastic approximation weak convergence Particle swarm optimization (PSO)
ISSN:	0018-9286, 1558-2523
Online-Zugang:	Volltext
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