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When the Decomposition Meets the Constraint Satisfaction Problem

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dc.abstract.enThis paper explores the joint use of decomposition methods and parallel computing for solving constraint satisfaction problems and introduces a framework called Parallel Decomposition for Constraint Satisfaction Problems (PD-CSP). The main idea is that the set of constraints are first clustered using a decomposition algorithm in which highly correlated constraints are grouped together. Next, parallel search of variables is performed on the produced clusters in a way that is friendly for parallel computing. In particular, for the first step, we propose the adaptation of two well-known clustering algorithms ( -means and DBSCAN). For the second step, we develop a GPU-based approach to efficiently explore the clusters. The results from the extensive experimental evaluation show that the PD-CSP provides competitive results in terms of accuracy and runtime.
dc.affiliationUniwersytet Warszawski
dc.contributor.authorHabbas, Zineb
dc.contributor.authorLin, Jerry Chun-Wei
dc.contributor.authorDjenouri, Youcef
dc.contributor.authorDjenouri, Djamel
dc.contributor.authorCano, Alberto
dc.contributor.authorMichalak, Tomasz
dc.date.accessioned2024-01-26T11:57:45Z
dc.date.available2024-01-26T11:57:45Z
dc.date.issued2020
dc.description.financePublikacja bezkosztowa
dc.description.volume8
dc.identifier.doi10.1109/ACCESS.2020.3038228
dc.identifier.issn2169-3536
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/124972
dc.identifier.weblinkhttp://xplorestaging.ieee.org/ielx7/6287639/8948470/09260140.pdf?arnumber=9260140
dc.languageeng
dc.pbn.affiliationcomputer and information sciences
dc.relation.ispartofIEEE Access
dc.relation.pages207034-207043
dc.rightsClosedAccess
dc.sciencecloudnosend
dc.titleWhen the Decomposition Meets the Constraint Satisfaction Problem
dc.typeJournalArticle
dspace.entity.typePublication