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Randomized Difference Two-Timescale Simultaneous Perturbation Stochastic Approximation Algorithms for Simulation Optimization of Hidden Markov Models

dc.contributor.advisorMarcus, Steven I.en_US
dc.contributor.advisorFu, Michael C.en_US
dc.contributor.authorBhatnagar, Shalabhen_US
dc.contributor.authorFu, Michael C.en_US
dc.contributor.authorMarcus, Steven I.en_US
dc.contributor.authorBhatnagar, Shashanken_US
dc.date.accessioned2007-05-23T10:09:19Z
dc.date.available2007-05-23T10:09:19Z
dc.date.issued2000en_US
dc.identifier.urihttp://hdl.handle.net/1903/6130
dc.description.abstractWe proposetwo finite difference two-timescale simultaneous perturbationstochastic approximation (SPSA)algorithmsfor simulation optimization ofhidden Markov models. Stability and convergence of both thealgorithms is proved.<p>Numericalexperiments on a queueing model with high-dimensional parameter vectorsdemonstrate orders of magnitude faster convergence using thesealgorithms over related $(N+1)$-Simulation finite difference analoguesand another two-simulation finite difference algorithm that updates incycles.en_US
dc.format.extent550623 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2000-13en_US
dc.subjectmathematical modelingen_US
dc.subjectsimulationen_US
dc.subjectoptimal controlen_US
dc.subjectoptimizationen_US
dc.subjectdiscrete event dynamical systems DEDSen_US
dc.subjectflexible manufacturingen_US
dc.subjectmanufacturingen_US
dc.subjectSimulation Optimizationen_US
dc.subjectHidden Markov Modelsen_US
dc.subjectTwo-Timescale SPSA Algorithmsen_US
dc.subjectIntelligent Control Systemsen_US
dc.subjectSystems Integration Methodologyen_US
dc.titleRandomized Difference Two-Timescale Simultaneous Perturbation Stochastic Approximation Algorithms for Simulation Optimization of Hidden Markov Modelsen_US
dc.typeTechnical Reporten_US
dc.contributor.departmentISRen_US


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