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Asymptotically Optimal Simulation Budget Allocation under Fixed Confidence Level by Ordinal Optimization

作者:WANGJian-feng; SUNChun-Lin; CHENYong-q...随机优化系统仿真序优化置信度最优分配

摘要:Ordinal optimization concentrates on isolating a subset of good designs with high probability and reduces the required simulation time dramatically for discrete event simulation. To obtain the same probability level,we may optimally allocate our computing budget among different designs,instead of equally simulating all different designs. In this paper we present an effective approach to optimally allocate computing budget for discrete-event system simulation. While ordinal optimization can dramatically reduce the computation cost, our approach can further reduce the already-low cost.

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