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dc.creatorLatorre Biel, Juan Ignacioes_ES
dc.creatorJiménez Macías, Emilioes_ES
dc.creatorPérez de la Parte, Mercedeses_ES
dc.creatorBlanco Fernández, Julioes_ES
dc.creatorMartínez Cámara, Eduardoes_ES
dc.date.accessioned2018-08-31T08:07:50Z
dc.date.available2018-08-31T08:07:50Z
dc.date.issued2014
dc.identifier.issn1085-3375 (Print)
dc.identifier.issn1687-0409 (Electronic)
dc.identifier.urihttps://hdl.handle.net/2454/30328
dc.description.abstractArtificial intelligence methodologies, as the core of discrete control and decision support systems, have been extensively applied in the industrial production sector. The resulting tools produce excellent results in certain cases; however, the NP-hard nature of many discrete control or decision making problems in the manufacturing area may require unaffordable computational resources, constrained by the limited available time required to obtain a solution. With the purpose of improving the efficiency of a control methodology for discrete systems, based on a simulation-based optimization and the Petri net (PN) model of the real discrete event dynamic system (DEDS), this paper presents a strategy, where a transformation applied to the model allows removing the redundant information to obtain a smaller model containing the same useful information. As a result, faster discrete optimizations can be implemented.This methodology is based on the use of a formalism belonging to the paradigmof thePNfor describingDEDS, the disjunctive colored PN. Furthermore, the metaheuristic of genetic algorithms is applied to the search of the best solutions in the solution space. As an illustration of the methodology proposal, its performance is compared with the classic approach on a case study, obtaining faster the optimal solution.en
dc.format.extent16 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherHindawien
dc.relation.ispartofAbstract and Applied Analysis, volume 2014, article ID 821707, 16 p.en
dc.rights© 2014 Juan-Ignacio Latorre-Biel et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.subjectPetri netsen
dc.subjectDiscrete event dynamic systems (DEDS)en
dc.subjectDiscrete optimizationen
dc.titleControl of discrete event systems by means of discrete optimization and disjunctive colored PNs: application to manufacturing facilitiesen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Ingeniería Mecánica, Energética y de Materialeses_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Mekanika, Energetika eta Materialen Ingeniaritza Sailaeu
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.identifier.doi10.1155/2014/821707
dc.relation.publisherversionhttps://doi.org/10.1155/2014/821707
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.type.versionVersión publicada / Argitaratu den bertsioaes


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© 2014 Juan-Ignacio Latorre-Biel et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as © 2014 Juan-Ignacio Latorre-Biel et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.