{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T11:56:43Z","timestamp":1772020603310,"version":"3.50.1"},"reference-count":34,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2008,8,22]],"date-time":"2008-08-22T00:00:00Z","timestamp":1219363200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,8,22]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>The proposed algorithm shows a competitive performance against the state\u2010of\u2010the\u2010art constrained optimization algorithms.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The proposed algorithm can be used to solve single objective problems with linear or non\u2010linear functions, and subject to both equality and inequality constraints which can be linear and non\u2010linear. In this paper, it is applied to various engineering design problems, and for the solution of state\u2010of\u2010the\u2010art benchmark problems.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1108\/17563780810893482","type":"journal-article","created":{"date-parts":[[2008,8,23]],"date-time":"2008-08-23T07:02:06Z","timestamp":1219474926000},"page":"425-453","source":"Crossref","is-referenced-by-count":27,"title":["Constrained optimization with an improved particle swarm optimization algorithm"],"prefix":"10.1108","volume":"1","author":[{"given":"Angel E.","family":"Mu\u00f1oz Zavala","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arturo","family":"Hern\u00e1ndez Aguirre","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrique R.","family":"Villa Diharce","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Salvador","family":"Botello Rionda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022012519464162800_b1","doi-asserted-by":"crossref","unstructured":"Angeline, P. 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