Set constraint model and automated encoding into SAT: application to the social golfer problem

dc.contributor.authorLardeux, F.es_ES
dc.contributor.authorMonfroy, E.es_ES
dc.contributor.authorCrawford, B.es_ES
dc.contributor.authorSoto, R.es_ES
dc.date.accessioned6/22/2022 13:33
dc.date.accessioned2022-09-30T16:09:26Z
dc.date.available6/22/2022 13:33
dc.date.available2022-09-30T16:09:26Z
dc.date.issued2015
dc.description.abstractOn the one hand, constraint satisfaction problems allow one to expressively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to expressively model set constraint problems and to encode them automatically into SAT instances. We apply our technique to the social golfer problem and we also use it to break symmetries of the problem. Our technique is simpler, more expressive, and less error-prone than direct modeling. The SAT instances that we automatically generate contain less clauses than improved direct instances such as in Triska and Musliu (Ann Oper Res 194(1):427–438, 2012), and with unit propagation they also contain less variables. Moreover, they are well-suited for SAT solvers and they are solved faster as shown when solving difficult instances of the social golfer problem. © 2015, Springer Science+Business Media New York.es_ES
dc.formatapplication/pdfes_ES
dc.identifier.doi10.1007/s10479-015-1914-5es_ES
dc.identifier.urihttps://doi.org/10.1007/s10479-015-1914-5
dc.language.isoenges_ES
dc.publisherSpringer New York LLCes_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_ES
dc.sourceAnnals of Operations Researches_ES
dc.subjectDecision Scienceses_ES
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#5.02.04es_ES
dc.titleSet constraint model and automated encoding into SAT: application to the social golfer problemes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
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