Autonomous tuning for constraint programming via artificial bee colony optimization

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dc.contributor.authorSoto, R.es_ES
dc.contributor.authorCrawford, B.es_ES
dc.contributor.authorMella F.es_ES
dc.contributor.authorFlores J.es_ES
dc.contributor.authorGalleguillos, C.es_ES
dc.contributor.authorMisra, S.es_ES
dc.contributor.authorJohnson, F.es_ES
dc.contributor.authorParedes, F.es_ES
dc.date.accessioned6/22/2022 14:20
dc.date.accessioned2022-06-22T20:03:32Z
dc.date.available6/22/2022 14:20
dc.date.available2022-06-22T20:03:32Z
dc.date.issued2015
dc.description.abstractConstraint Programming allows the resolution of complex problems, mainly combinatorial ones. These problems are defined by a set of variables that are subject to a domain of possible values and a set of constraints. The resolution of these problems is carried out by a constraint satisfaction solver which explores a search tree of potential solutions. This exploration is controlled by the enumeration strategy, which is responsible for choosing the order in which variables and values are selected to generate the potential solution. Autonomous Search provides the ability to the solver to self-tune its enumeration strategy in order to select the most appropriate one for each part of the search tree. This self-tuning process is commonly supported by an optimizer which attempts to maximize the quality of the search process, that is, to accelerate the resolution. In this work, we present a new optimizer for self-tuning in constraint programming based on artificial bee colonies. We report encouraging results where our autonomous tuning approach clearly improves the performance of the resolution process. © Springer International Publishing Switzerland 2015.es_ES
dc.formatapplication/pdfes_ES
dc.identifier.doi10.1007/978-3-319-21404-7_12es_ES
dc.identifier.urihttps://doi.org/10.1007/978-3-319-21404-7_12
dc.language.isoen_USes_ES
dc.publisherSpringer Verlages_ES
dc.publisher.countryDEes_ES
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)es_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)es_ES
dc.subjectComputer Sciencees_ES
dc.subjectMathematicses_ES
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#2.02.04es_ES
dc.titleAutonomous tuning for constraint programming via artificial bee colony optimizationes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
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