Documents disponibles écrits par cet auteur

The challenge of optimizing expensive black boxes / M. Laguna in Journal of the operational research society (JORS), Vol. 61 N° 1 (Issue spécial) (Janvier 2010) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 61 N° 1 (Issue spécial) (Janvier 2010) . - pp. 53–67 Titre : The challenge of optimizing expensive black boxes : a scatter search/rough set theory approach Type de document : texte imprimé Auteurs : M. Laguna, Auteur ; J. Molina, Auteur ; F. Pérez, Auteur Année de publication : 2011 Article en page(s) : pp. 53–67 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Black-box  optimization  Simulation  optimization  Scatter  search  Rough  sets Index. décimale : 001.424 Résumé : There is renewed interest in the development of effective and efficient methods for optimizing models of which the optimizer has no structural knowledge. This is what in the literature is referred to as optimization of black boxes. In particular, we address the challenge of optimizing expensive black boxes, that is, those that require a significant computational effort to be evaluated. We describe the use of rough set theory within a scatter search framework, with the goal of identifying high-quality solutions with a limited number of objective function evaluations. The rough set strategies that we developed take advantage of the information provided by the best and diverse solutions found during the search, in order to define areas of the solution space that are promising for search intensification. We test our procedure on a set of 92 nonlinear multimodal functions of varied complexity and size and compare the results with a state-of-the-art procedure based on particle swarm optimization. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n1/abs/jors2009124a.html [article] The challenge of optimizing expensive black boxes : a scatter search/rough set theory approach [texte imprimé] / M. Laguna, Auteur ; J. Molina, Auteur ; F. Pérez, Auteur . - 2011 . - pp. 53–67. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 61 N° 1 (Issue spécial) (Janvier 2010) . - pp. 53–67 Mots-clés : Black-box  optimization  Simulation  optimization  Scatter  search  Rough  sets Index. décimale : 001.424 Résumé : There is renewed interest in the development of effective and efficient methods for optimizing models of which the optimizer has no structural knowledge. This is what in the literature is referred to as optimization of black boxes. In particular, we address the challenge of optimizing expensive black boxes, that is, those that require a significant computational effort to be evaluated. We describe the use of rough set theory within a scatter search framework, with the goal of identifying high-quality solutions with a limited number of objective function evaluations. The rough set strategies that we developed take advantage of the information provided by the best and diverse solutions found during the search, in order to define areas of the solution space that are promising for search intensification. We test our procedure on a set of 92 nonlinear multimodal functions of varied complexity and size and compare the results with a state-of-the-art procedure based on particle swarm optimization. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n1/abs/jors2009124a.html