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Robust parameter design optimization of simulation experiments using stochastic perturbation methods / Miranda, A. K. in Journal of the operational research society (JORS), Vol. 62 N° 1 (Janvier 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 1 (Janvier 2011) . - pp. 198–205 Titre : Robust parameter design optimization of simulation experiments using stochastic perturbation methods Type de document : texte imprimé Auteurs : Miranda, A. K., Auteur ; Del Castillo, E., Auteur Année de publication : 2011 Article en page(s) : pp. 198–205 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Simulation  optimization  Noise  factors  Crossed  arrays  Non-homogeneous  variance Index. décimale : 001.424 Résumé : Stochastic perturbation methods can be applied to problems for which either the objective function is represented analytically, or the objective function is the result of a simulation experiment. The Simultaneous Perturbation Stochastic Approximation (SPSA) method has the advantage over similar methods of requiring only two measurements at each iteration of the search. This feature makes SPSA attractive for robust parameter design (RPD) problems where some factors affect the variance of the response(s) of interest. In this paper, the feasibility of SPSA as a RPD optimizer is presented, first when the objective function is known, and then when the objective function is estimated by means of a discrete-event simulation. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n1/abs/jors2009163a.html [article] Robust parameter design optimization of simulation experiments using stochastic perturbation methods [texte imprimé] / Miranda, A. K., Auteur ; Del Castillo, E., Auteur . - 2011 . - pp. 198–205. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 1 (Janvier 2011) . - pp. 198–205 Mots-clés : Simulation  optimization  Noise  factors  Crossed  arrays  Non-homogeneous  variance Index. décimale : 001.424 Résumé : Stochastic perturbation methods can be applied to problems for which either the objective function is represented analytically, or the objective function is the result of a simulation experiment. The Simultaneous Perturbation Stochastic Approximation (SPSA) method has the advantage over similar methods of requiring only two measurements at each iteration of the search. This feature makes SPSA attractive for robust parameter design (RPD) problems where some factors affect the variance of the response(s) of interest. In this paper, the feasibility of SPSA as a RPD optimizer is presented, first when the objective function is known, and then when the objective function is estimated by means of a discrete-event simulation. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n1/abs/jors2009163a.html