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dc.contributor.authorGabriel, Luque
dc.contributor.authorEnrique, Alba
dc.date.accessioned2014-07-08T11:02:16Z
dc.date.available2014-07-08T11:02:16Z
dc.date.issued2014-07-08
dc.identifier.urihttp://hdl.handle.net/10630/7787
dc.description.abstractThis paper proposes a novel algorithm combining path relinking with a set of cooperating trajectory based parallel algorithms to yield a new metaheuristic of enhanced search features. Algorithms based on the exploration of the neighborhood of a single solution, like simulated annealing (SA), have offered accurate results for a large number of real-world problems in the past. Because of their trajectory based nature, some advanced models such as the cooperative one are competitive in academic problems, but still show many limitations in addressing large scale instances. In addition, the field of parallel models for trajectory methods has not deeply been studied yet (at least in comparison with parallel population based models). In this work, we propose a new hybrid algorithm which improves cooperative single solution techniques by using path relinking, allowing both to reduce the global execution time and to improve the efficacy of the method. We test here this new model using a large benchmark of instances of two well-known NP-hard problems: MAXSAT and QAP, with competitive results.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectComputación evolutivaes_ES
dc.subject.otherParallelismes_ES
dc.subject.otherTrajectory based metaheuristicses_ES
dc.subject.otherPath relinkinges_ES
dc.titleEnhancing Parallel Cooperative Trajectory Based Metaheuristics with Path Relinkinges_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitleGenetic and Evolutionary Computation Conference 2014es_ES
dc.relation.eventplaceVancouver, Canadaes_ES
dc.relation.eventdateJulio 2014es_ES


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