dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorEcheverri, Mauricio Granada
dc.creatorLópez Lezama, Jesús María
dc.creatorRomero, Ruben
dc.date2014-05-27T11:23:57Z
dc.date2016-10-25T18:27:20Z
dc.date2014-05-27T11:23:57Z
dc.date2016-10-25T18:27:20Z
dc.date2009-09-01
dc.date.accessioned2017-04-06T01:36:51Z
dc.date.available2017-04-06T01:36:51Z
dc.identifierRevista Facultad de Ingenieria, n. 49, p. 141-150, 2009.
dc.identifier0120-6230
dc.identifierhttp://hdl.handle.net/11449/71119
dc.identifierhttp://acervodigital.unesp.br/handle/11449/71119
dc.identifierWOS:000269084600015
dc.identifier2-s2.0-70350412280.pdf
dc.identifier2-s2.0-70350412280
dc.identifierhttp://aprendeenlinea.udea.edu.co/revistas/index.php/ingenieria/article/viewArticle/15968
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/892140
dc.descriptionThis paper presents a new approach for solving constraint optimization problems (COP) based on the philosophy of lexicographical goal programming. A two-phase methodology for solving COP using a multi-objective strategy is used. In the first phase, the objective function is completely disregarded and the entire search effort is directed towards finding a single feasible solution. In the second phase, the problem is treated as a bi-objective optimization problem, turning the constraint optimization into a two-objective optimization. The two resulting objectives are the original objective function and the constraint violation degree. In the first phase a methodology based on progressive hardening of soft constraints is proposed in order to find feasible solutions. The performance of the proposed methodology was tested on 11 well-known benchmark functions.
dc.languagespa
dc.relationRevista Facultad de Ingenieria
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectConstraint optimization
dc.subjectEvolutionary algorithms
dc.subjectMulti-objective algorithms
dc.titleUna metodología eficiente para manejo de restricciones en algoritmos evolutivos multi-objetivo
dc.typeOtro


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