Constrained optimization with an improved particle swarm optimization algorithm

Purpose - The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.Design methodology approach - This paper introduces a hybrid approach based on a modified ring neighborhood with two new perturbation operators d...

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Vydané v:International journal of intelligent computing and cybernetics Ročník 1; číslo 3; s. 425 - 453
Hlavní autori: Muñoz Zavala, Angel E., Hernández Aguirre, Arturo, Villa Diharce, Enrique R., Botello Rionda, Salvador
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Bingley Emerald Group Publishing Limited 22.08.2008
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ISSN:1756-378X, 1756-3798
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Shrnutí:Purpose - The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.Design methodology approach - This paper introduces a hybrid approach based on a modified ring neighborhood with two new perturbation operators designed to keep diversity. A constraint handling technique based on feasibility and sum of constraints violation is adopted. Also, a special technique to handle equality constraints is proposed.Findings - The paper shows that it is possible to improve PSO and keeping the advantages of its social interaction through a simple idea: perturbing the PSO memory.Research limitations implications - The proposed algorithm shows a competitive performance against the state-of-the-art constrained optimization algorithms.Practical implications - The proposed algorithm can be used to solve single objective problems with linear or non-linear functions, and subject to both equality and inequality constraints which can be linear and non-linear. In this paper, it is applied to various engineering design problems, and for the solution of state-of-the-art benchmark problems.Originality value - A new neighborhood structure for PSO algorithm is presented. Two perturbation operators to improve PSO algorithm are proposed. A special technique to handle equality constraints is proposed.
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ISSN:1756-378X
1756-3798
DOI:10.1108/17563780810893482