Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/2373
Full metadata record
DC FieldValueLanguage
dc.contributor.authorG. Wimanen
dc.contributor.authorGustavo Schweickardten
dc.contributor.authorVladimiro Mirandaen
dc.date.accessioned2017-11-16T13:35:01Z-
dc.date.available2017-11-16T13:35:01Z-
dc.date.issued2011en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/2373-
dc.description.abstractMetaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multiobjective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.en
dc.languageengen
dc.relation208en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.titleA comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systemsen
dc.typearticleen
dc.typePublicationen
Appears in Collections:CPES - Articles in International Journals

Files in This Item:
File Description SizeFormat 
PS-07504.pdf188.94 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.