Autonomous Tuning for Constraint Programming Via Artificial Bee Colony Optimization

dc.authorid johnson, franklin/0000-0003-4522-3809
dc.authorid Misra, Sanjay/0000-0002-3556-9331
dc.authorid Crawford, Broderick/0000-0001-5500-0188
dc.authorid Galleguillos, Cristian/0000-0001-9460-8719
dc.authorscopusid 24403038600
dc.authorscopusid 23395875300
dc.authorscopusid 56971288300
dc.authorscopusid 57198032485
dc.authorscopusid 55761197000
dc.authorscopusid 56962766700
dc.authorscopusid 15520434500
dc.authorwosid johnson, franklin/AAQ-1436-2020
dc.authorwosid Misra, Sanjay/K-2203-2014
dc.authorwosid Galleguillos, Cristian/C-7756-2014
dc.contributor.author Soto, Ricardo
dc.contributor.author Crawford, Broderick
dc.contributor.author Mella, Felipe
dc.contributor.author Flores, Javier
dc.contributor.author Galleguillos, Cristian
dc.contributor.author Misra, Sanjay
dc.contributor.author Paredes, Fernando
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-07-05T14:32:11Z
dc.date.available 2024-07-05T14:32:11Z
dc.date.issued 2015
dc.department Atılım University en_US
dc.department-temp [Soto, Ricardo; Crawford, Broderick; Mella, Felipe; Flores, Javier; Galleguillos, Cristian] Pontificia Univ Catolica Valparaiso, Valparaiso, Chile; [Soto, Ricardo] Univ Autonoma Chile, Santiago, Chile; [Soto, Ricardo] Univ Cient Sur, Lima, Peru; [Crawford, Broderick] Univ San Sebastian, Santiago, Chile; [Crawford, Broderick] Univ Cent Chile, Santiago, Chile; [Misra, Sanjay] Atilim Univ, Ankara, Turkey; [Johnson, Franklin] Univ Playa Ancha, Valparaiso, Chile; [Paredes, Fernando] Univ Diego Portales, Escuela Ingn Ind, Santiago, Chile en_US
dc.description johnson, franklin/0000-0003-4522-3809; Misra, Sanjay/0000-0002-3556-9331; Crawford, Broderick/0000-0001-5500-0188; Galleguillos, Cristian/0000-0001-9460-8719 en_US
dc.description.abstract Constraint 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. en_US
dc.identifier.citationcount 2
dc.identifier.doi 10.1007/978-3-319-21404-7_12
dc.identifier.endpage 171 en_US
dc.identifier.isbn 9783319214047
dc.identifier.isbn 9783319214030
dc.identifier.issn 0302-9743
dc.identifier.issn 1611-3349
dc.identifier.scopus 2-s2.0-84948979394
dc.identifier.startpage 159 en_US
dc.identifier.uri https://doi.org/10.1007/978-3-319-21404-7_12
dc.identifier.uri https://hdl.handle.net/20.500.14411/751
dc.identifier.volume 9155 en_US
dc.identifier.wos WOS:000364988700012
dc.institutionauthor Mısra, Sanjay
dc.language.iso en en_US
dc.publisher Springer-verlag Berlin en_US
dc.relation.ispartof 15th International Conference on Computational Science and Its Applications (ICCSA) -- JUN 22-25, 2015 -- Banff, CANADA en_US
dc.relation.ispartofseries Lecture Notes in Computer Science
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 3
dc.subject Artificial intelligence en_US
dc.subject Optimization en_US
dc.subject Adaptive systems en_US
dc.subject Metaheuristics en_US
dc.title Autonomous Tuning for Constraint Programming Via Artificial Bee Colony Optimization en_US
dc.type Conference Object en_US
dc.wos.citedbyCount 2
dspace.entity.type Publication
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