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https://doi.org/10.1109/WSC.2011.6148116
Title: | Optimal sampling laws for constrained simulation optimization on finite sets: The bivariate normal case | Authors: | Hunter, S.R. Chen, C.-H. Pasupathy, R. Pujowidianto, N.A. Lee, L.H. Yap, C.M. |
Issue Date: | 2011 | Citation: | Hunter, S.R.,Chen, C.-H.,Pasupathy, R.,Pujowidianto, N.A.,Lee, L.H.,Yap, C.M. (2011). Optimal sampling laws for constrained simulation optimization on finite sets: The bivariate normal case. Proceedings - Winter Simulation Conference : 4289-4297. ScholarBank@NUS Repository. https://doi.org/10.1109/WSC.2011.6148116 | Abstract: | Consider the context of selecting an optimal system from amongst a finite set of competing systems, based on a "stochastic" objective function and subject to a single "stochastic" constraint. In this setting, and assuming the objective and constraint performance measures have a bivariate normal distribution, we present a characterization of the optimal sampling allocation across systems. Unlike previous work on this topic, the characterized optimal allocations are asymptotically exact and expressed explicitly as a function of the correlation between the performance measures. © 2011 IEEE. | Source Title: | Proceedings - Winter Simulation Conference | URI: | http://scholarbank.nus.edu.sg/handle/10635/72365 | ISBN: | 9781457721083 | ISSN: | 08917736 | DOI: | 10.1109/WSC.2011.6148116 |
Appears in Collections: | Staff Publications |
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