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dc.contributor.authorOchoa, Gabriela
dc.contributor.authorChicano, Francisco 
dc.date.accessioned2019-07-22T10:07:27Z
dc.date.available2019-07-22T10:07:27Z
dc.date.created2019
dc.date.issued2019-07-22
dc.identifier.urihttps://hdl.handle.net/10630/18105
dc.description.abstractLocal Optima Networks (LONs) are a valuable tool to understand fitness landscapes of optimization problems observed from the perspective of a search algorithm. Local optima of the optimization problem are linked by an edge in LONs when an operation in the search algorithm allows one of them to be reached from the other. Previous work analyzed several combinatorial optimization problems using LONs and provided a visual guide to understand why the instances are difficult or easy for the search algorithms. In this work we analyze for the first time the MAX-SAT problem. Given a Boolean formula in Conjunctive Normal Form, the goal of the MAX-SAT problem is to find an assignment maximizing the number of satistified clauses. Several random and industrial instances of MAX-SAT are analyzed using Iterated Local Search to sample the search space.en_US
dc.description.sponsorshipUniversidad de Málaga, Campus de Excelencia International Andalucía Tech. Universidad de Stirling, Reino Unido. Ministerio de Economía y Competitividad y FEDER (proyecto TIN2017-88213-R).en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/*
dc.subjectOptimización combinatoriaen_US
dc.subjectComputación evolutivaen_US
dc.subjectCongresos y conferenciasen_US
dc.subject.otherLocal Optima Networksen_US
dc.subject.otherMAX-SATen_US
dc.subject.otherCombinatorial Optimizationen_US
dc.subject.otherFunnelsen_US
dc.titleLocal Optima Network Analysis for MAX-SATen_US
dc.typeinfo:eu-repo/semantics/preprinten_US
dc.centroE.T.S.I. Informáticaen_US
dc.relation.eventtitleGenetic and Evolutionary Computation Conferenceen_US
dc.relation.eventplacePraga, República Checaen_US
dc.relation.eventdate13 de julio de 2019en_US
dc.rights.ccAtribución-CompartirIgual 4.0 Internacional*


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