000029035 001__ 29035
000029035 005__ 20130605083003.0
000029035 0248_ $$aoai:doc.rero.ch:20120427143923-SC$$ppostprint$$prero_explore$$pcdu33$$zcdu34$$zthesis_urn$$zreport$$zthesis$$zbook$$zjournal$$zcdu16$$zhegge$$zpreprint$$zcdu1$$zdissertation
000029035 041__ $$aeng
000029035 080__ $$a33
000029035 100__ $$aFilar, J.-A.$$uSch. of Math., Univ. of South Australia, Adelaide
000029035 245__ $$9eng$$aDecomposition and parallel processing techniques for two-time scale controlled Markov chains
000029035 269__ $$c2000
000029035 520__ $$9eng$$aDeals with a class of ergodic control problems for systems described by Markov chains with strong and weak interactions. These systems are composed of a set of m subchains that are weakly coupled. Using results established by Abbad et al. (1992). We formulate a limit control problem the solution of which can be obtained via an associated nondifferentiable convex programming (NDCP) problem. The technique used to solve the NDCP problem is the analytic center cutting plane method (ACCPM) which implements a dialogue between, on one hand, a master program computing the analytical center of a localization set containing the solution and, on the other hand, an oracle proposing cutting planes that reduce the size of the localization set at each main iteration. The interesting aspect of this implementation comes from two characteristics: (i) the oracle proposes cutting planes by solving reduced sized Markov decision problems (MDP) via a linear program (LP) or a policy iteration method; (ii) several cutting planes can be proposed simultaneously through a parallel implementation on m processors. The paper concentrates on these two aspects and shows, on a large scale MDP obtained from the numerical approximation “a la Kushner-Dupuis” of a singularly perturbed hybrid stochastic control problem, the important computational speed-up obtained
000029035 695__ $$9eng$$aMarkov processes ; convex programming ; decision theory ; linear programming ; parallel processing ; singularly perturbed systems ; stochastic systems
000029035 700__ $$aGondzio, J.$$uDepartment of Mathematics & Statistics, The University of Edinburgh, UK
000029035 700__ $$aHaurie, Alain$$uUniversité de Genève
000029035 700__ $$aMoresino, Francesco$$uHaute école de gestion de Genève
000029035 700__ $$aVial, J.-P.$$uUniversité de Genève
000029035 773__ $$g2000/1//711-716$$tProceedings of the 39th IEEE Conference on Decision and Control, 2000
000029035 8564_ $$fMoresino_2000_decomposition.pdf$$qapplication/pdf$$s548483$$uhttp://doc.rero.ch/record/29035/files/Moresino_2000_decomposition.pdf$$yorder:1$$zTexte intégral
000029035 918__ $$aHaute école de gestion de Genève$$bCampus de Battelle, Bâtiment F, 7 route de Drize, 1227 Carouge$$cCentre de recherche appliqué en gestion (CRAG)
000029035 919__ $$aHaute école de gestion de Genève$$bGenève$$ddoc.support@rero.ch
000029035 980__ $$aPOSTPRINT$$bHEGGE$$fART_INPROC
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