Simulation Budget Allocation for Further Enhancing theEfficiency of Ordinal Optimization
Discrete Event Dynamic Systems
A large deviations perspective on ordinal optimization
WSC '04 Proceedings of the 36th conference on Winter simulation
A new perspective on feasibility determination
Proceedings of the 40th Conference on Winter Simulation
Finding feasible systems in the presence of constraints on multiple performance measures
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Introduction to Rare Event Simulation
Introduction to Rare Event Simulation
Discrete-valued, stochastic-constrained simulation optimization with compass
Proceedings of the Winter Simulation Conference
Asymptotic Simulation Efficiency Based on Large Deviations
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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We consider the problem of selecting an optimal system from among a finite set of competing systems, based on a "stochastic" objective function and subject to a single "stochastic" constraint. By strategically dividing the competing systems, we derive a large deviations sampling framework that asymptotically minimizes the probability of false selection. We provide an illustrative example where a closed-form sampling law is obtained after relaxation.