Experiments in Parallel Constraint-Based Local Search

dc.contributor.authorCaniou, Yves
dc.contributor.authorCodognet, Philippe
dc.contributor.authorDiaz, Daniel
dc.contributor.authorAbreu, Salvador
dc.contributor.editorMerz, Peter
dc.contributor.editorHao, Jin-Kao
dc.date.accessioned2012-01-30T16:05:34Z
dc.date.available2012-01-30T16:05:34Z
dc.date.issued2011
dc.description.abstractWe present a parallel implementation of a constraint-based local search algorithm and investigate its performance results on hardware with several hundreds of processors. We choose as basic constraint solving algorithm for these experiments the ”adaptive search” method, an efficient sequential local search method for Constraint Satisfaction Problems. The implemented algorithm is a parallel version of adaptive search in a multiple independent-walk manner, that is, each process is an independent search engine and there is no communication between the simultaneous computations. Preliminary performance evaluation on a variety of classical CSPs benchmarks shows that speedups are very good for a few tens of processors, and good up to a few hundreds of processors.por
dc.identifier.authoremailnd
dc.identifier.authoremailnd
dc.identifier.authoremailnd
dc.identifier.authoremailspa@di.uevora.pt
dc.identifier.citationYves Caniou and Philippe Codognet and Daniel Diaz and Salvador Abreu, Experiments in Parallel Constraint-Based Local Search, , Evolutionary Computation in Combinatorial Optimization - 11th European Conference (EvoCOP 2011), LNCS, Springer, Vol. 6622, Pag. 96-107, 2011.por
dc.identifier.doi10.1007/978-3-642-20364-0_9
dc.identifier.urihttp://hdl.handle.net/10174/4561
dc.language.isoengpor
dc.peerreviewedyespor
dc.rightsopenAccesspor
dc.subjectConstraint Satisfactionpor
dc.subjectParallel Computationpor
dc.titleExperiments in Parallel Constraint-Based Local Searchpor
dc.typearticlepor
degois.publication.titleEvolutionary Computation in Combinatorial Optimization - 11th European Conference, EvoCOP 2011, Torino, Italy, April 27-29, 2011por

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