Show simple item record

dc.contributor.authorSzechtman, Roberto
dc.contributor.authorYucesan, Enver
dc.date.accessioned2014-01-29T23:39:08Z
dc.date.available2014-01-29T23:39:08Z
dc.date.issued2008
dc.identifier.urihttp://hdl.handle.net/10945/38580
dc.descriptionProceedings of the 2008 Winter Simulation Conference S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds.en_US
dc.description.abstractWe consider the problem of feasibility determination in a stochastic setting. In particular, we wish to determine whether a system belongs to a given set G 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.typeConference Paperen_US
dc.contributor.departmentOperations Research (OR)


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record