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Article: Nature-inspired particle mechanics algorithm for multi-objective optimization

TitleNature-inspired particle mechanics algorithm for multi-objective optimization
Authors
Issue Date2009
Citation
Studies In Computational Intelligence, 2009, v. 171, p. 255-277 How to Cite?
AbstractIn many real world optimization problems, several optimization goals have to be considered in parallel. For this reason, there has been a growing interest in multi-objective optimization (MOO) in the past many years. Several new approaches have recently been proposed, which produced very good results. However, existing techniques have solved mainly problems of "low dimension", i.e., with less than 10 optimization objectives. This chapter proposes a new computational algorithm whose design is inspired by particle mechanics in physics. The algorithm is capable of solving MOO problems of high dimensions. There is a deep and useful connection between particle mechanics and high dimensional MOO. This connection exposes new information and provides an unfamiliar perspective on traditional optimization problems and approaches. The alternative of particle mechanics algorithm (PMA) to traditional approaches can deal with a variety of complicated, large scale, high dimensional MOO problems. © 2009 Springer-Verlag Berlin Heidelberg.
Persistent Identifierhttp://hdl.handle.net/10722/152407
ISSN
2015 SCImago Journal Rankings: 0.187
References

 

DC FieldValueLanguage
dc.contributor.authorFeng, Xen_US
dc.contributor.authorLau, FCen_US
dc.date.accessioned2012-06-26T06:38:08Z-
dc.date.available2012-06-26T06:38:08Z-
dc.date.issued2009en_US
dc.identifier.citationStudies In Computational Intelligence, 2009, v. 171, p. 255-277en_US
dc.identifier.issn1860-949Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/152407-
dc.description.abstractIn many real world optimization problems, several optimization goals have to be considered in parallel. For this reason, there has been a growing interest in multi-objective optimization (MOO) in the past many years. Several new approaches have recently been proposed, which produced very good results. However, existing techniques have solved mainly problems of "low dimension", i.e., with less than 10 optimization objectives. This chapter proposes a new computational algorithm whose design is inspired by particle mechanics in physics. The algorithm is capable of solving MOO problems of high dimensions. There is a deep and useful connection between particle mechanics and high dimensional MOO. This connection exposes new information and provides an unfamiliar perspective on traditional optimization problems and approaches. The alternative of particle mechanics algorithm (PMA) to traditional approaches can deal with a variety of complicated, large scale, high dimensional MOO problems. © 2009 Springer-Verlag Berlin Heidelberg.en_US
dc.languageengen_US
dc.relation.ispartofStudies in Computational Intelligenceen_US
dc.titleNature-inspired particle mechanics algorithm for multi-objective optimizationen_US
dc.typeArticleen_US
dc.identifier.emailLau, FC:fcmlau@cs.hku.hken_US
dc.identifier.authorityLau, FC=rp00221en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/978-3-540-88051-6_12en_US
dc.identifier.scopuseid_2-s2.0-58149229383en_US
dc.identifier.hkuros211460-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-58149229383&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume171en_US
dc.identifier.spage255en_US
dc.identifier.epage277en_US
dc.publisher.placeGermanyen_US
dc.identifier.scopusauthoridFeng, X=55200149100en_US
dc.identifier.scopusauthoridLau, FC=7102749723en_US

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