Gradient-Based Myopic Allocation Policy: An Efficient Sampling Procedure in a Low-Confidence Scenario

In this note, we study a simulation optimization problem of selecting the alternative with the best performance from a finite set, or a so-called ranking and selection problem, in a special low-confidence scenario. The most popular sampling allocation procedures in ranking and selection do not perfo...

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Veröffentlicht in:	IEEE transactions on automatic control 2018-09, Vol.63 (9), p.3091-3097
Hauptverfasser:	Peng, Yijie, Chen, Chun-Hung, Fu, Michael C., Hu, Jian-Qiang
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes methods Bayesian framework Computer simulation Confidence Correlation Gaussian distribution myopic allocation policy (MAP) Ranking ranking and selection Resource management Sampling simulation Taylor series
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