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dc.contributor.authorChicano, Francisco 
dc.contributor.authorWhitley, L. Darrell
dc.contributor.authorTinós, Renato
dc.date.accessioned2016-04-06T10:52:09Z
dc.date.available2016-04-06T10:52:09Z
dc.date.created2016
dc.date.issued2016-04-06
dc.identifier.urihttp://hdl.handle.net/10630/11122
dc.descriptionChicano, F., Whitley D., & Tinós R. (2016). Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization. 16th European Conference on Evolutionary Computation for Combinatorial Optimization (LNCS 9595), pp. 88-103es_ES
dc.description.abstractLocal search algorithms and iterated local search algorithms are a basic technique. Local search can be a stand-alone search method, but it can also be hybridized with evolutionary algorithms. Recently, it has been shown that it is possible to identify improving moves in Hamming neighborhoods for k-bounded pseudo-Boolean optimization problems in constant time. This means that local search does not need to enumerate neighborhoods to find improving moves. It also means that evolutionary algorithms do not need to use random mutation as a operator, except perhaps as a way to escape local optima. In this paper, we show how improving moves can be identified in constant time for multiobjective problems that are expressed as k-bounded pseudo-Boolean functions. In particular, multiobjective forms of NK Landscapes and Mk Landscapes are considered.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Fulbright program, Ministerio de Educación (CAS12/00274), Ministerio de Economía y Competitividad (TIN2014-57341-R), Air Force Office of Scientific Research, Air Force Materiel Command, USAF (FA9550-11-1-0088), FAPESP (2015/06462-1) and CNPq.es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectOptimización matemáticaes_ES
dc.subjectProgramación (Matemáticas)es_ES
dc.subject.otherHamming Ball Hill Climberes_ES
dc.subject.otherDelta Evaluationes_ES
dc.subject.otherMulti-Objective Optimizationes_ES
dc.subject.otherLocal Searches_ES
dc.titleEfficient Hill Climber for Multi-Objective Pseudo-Boolean Optimizationes_ES
dc.typeinfo:eu-repo/semantics/preprintes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitleEuropean Conference on Evolutionary Computation in Combinatorial Optimizationes_ES
dc.relation.eventplacePorto, Portugales_ES
dc.relation.eventdate30 de Marzo de 2016es_ES
dc.identifier.orcid0000-0003-1259-2990es_ES
dc.cclicenseby-nc-ndes_ES


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