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dc.contributor.authorSzechtman, Roberto
dc.contributor.authorYucesan, Enver
dc.dateWinter 2008
dc.date.accessioned2014-01-22T20:25:52Z
dc.date.available2014-01-22T20:25:52Z
dc.date.issued2008
dc.identifier.citation2008. A New Perspective on Feasibility Determination. Proceedings of the 2008 Winter Simulation Conference, pp 273-280. (With E. Yucesan)
dc.identifier.urihttp://hdl.handle.net/10945/38431
dc.descriptionProceedings of the 2008 Winter Simulation Conference, pp 273-280en_US
dc.description.abstractWe consider the problem of the feasibility determination in a stochastic setting. In particular, we wish to determine whether a system belongs to a given set based on a performance measure estimated through Monte Carlo simulation Our contribution is two-fold: (i) we characterize fractional allocations that are asymptotically optimal; and (ii) we provide an easily implementable algorithm, rooted in stochastic approximation theory, that results in sampling allocations that provably achieve in the limit the same performance as the optimal allocations. The finite-time behavior of the algorithm is also illustrated on two small examples.en_US
dc.rightsdefined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleA New Perspective on Feasibility Determinationen_US
dc.typeArticleen_US
dc.contributor.departmentOperations Research (OR)


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