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dc.contributor.authorCeberio Uribe, Josu ORCID
dc.contributor.authorIrurozki, Ekhine
dc.contributor.authorMendiburu Alberro, Alexander
dc.contributor.authorLozano Alonso, José Antonio ORCID
dc.date.accessioned2011-11-11T18:48:20Z
dc.date.available2011-11-11T18:48:20Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10810/4764
dc.description.abstractEstimation of Distribution Algorithms (EDAs) are a set of algorithms that belong to the field of Evolutionary Computation. Characterized by the use of probabilistic models to represent the solutions and the dependencies between the variables of the problem, these algorithms have been applied to a wide set of academic and real-world optimization problems, achieving competitive results in most scenarios. Nevertheless, there are some optimization problems, whose solutions can be naturally represented as permutations, for which EDAs have not been extensively developed. Although some work has been carried out in this direction, most of the approaches are adaptations of EDAs designed for problems based on integer or real domains, and only a few algorithms have been specifically designed to deal with permutation-based problems. In order to set the basis for a development of EDAs in permutation-based problems similar to that which occurred in other optimization fields (integer and real-value problems), in this paper we carry out a thorough review of state-of-the-art EDAs applied to permutation-based problems. Furthermore, we provide some ideas on probabilistic modeling over permutation spaces that could inspire the researchers of EDAs to design new approaches for these kinds of problems.es
dc.language.isoenges
dc.relation.ispartofseriesEHU-KZAA-TR;2011-05
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.titleA review on Estimation of Distribution Algorithms in Permutation-based Combinatorial Optimization Problemses
dc.typeinfo:eu-repo/semantics/reportes
dc.departamentoesCiencia de la computación e inteligencia artificiales_ES
dc.departamentoeuKonputazio zientziak eta adimen artifizialaes_ES


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