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dc.contributor.authorRoyset, J.O.
dc.contributor.authorPolak, E.
dc.dateJuly 2004
dc.date.accessioned2016-05-18T19:54:39Z
dc.date.available2016-05-18T19:54:39Z
dc.date.issued2004-07
dc.identifier.citationJ.O. Royset and E. Polak, 2004, “Implementable Algorithm for Stochastic Optimization using Sample Average Approximations,” Journal of Optimization Theory and Applications, Vol. 122, No. 1, pp. 157-184.en_US
dc.identifier.urihttp://hdl.handle.net/10945/48689
dc.description.abstractWe develop an implementable algorithm for stochastic optimization problems involving probability functions. Such problems arise in the design of structural and mechanical systems. The algorithm consists of a nonlinear optimization algorithm applied to sample average approximations and a precision-adjustment rule. The sample average approximations are constructed using Monte Carlo simulations or importance sampling techniques. We prove that the algorithm converges to a solution with probability one and illustrate its use by an example involving a reliability-based optimal design.en_US
dc.description.sponsorshipResearch Associateship Program at the National Research Councilen_US
dc.description.sponsorshipTaisei Chair in Civil Engineering at UC Berkeleyen_US
dc.description.sponsorshipNational Science Foundation under Grant ECS-9900985en_US
dc.format.extent28 p.en_US
dc.publisherPlenum Publishing Corporationen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleImplementable Algorithm for Stochastic Optimization Using Sample Average Approximationsen_US
dc.typeArticleen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)en_US
dc.contributor.departmentOperations Research (OR)en_US
dc.subject.authorStochastic optimizationen_US
dc.subject.authorsample average approximationsen_US
dc.subject.authorMonte Carlo simulationsen_US
dc.subject.authorreliability-based optimal designsen_US
dc.description.funderResearch Associateship Program at the National Research Councilen_US
dc.description.funderTaisei Chair in Civil Engineering at UC Berkeleyen_US
dc.description.funderNational Science Foundation under Grant ECS-9900985en_US


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