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Optimal computing budget allocation for complete ranking with input uncertainty

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  • Hui Xiao
  • Fei Gao
  • Loo Hay Lee

Abstract

Existing research in ranking and selection has focused on the problem of selecting the best design, subset selection and selecting the set of Pareto designs. Few works have addressed the problem of complete ranking. In this research, we consider the problem of ranking all alternatives completely with consideration of input uncertainty. Given a fixed simulation budget, we aim to maximize the probability of correct ranking among all designs based on their worst-case performances. The problem is formulated as an optimal computing budget allocation model. To make this optimization problem computationally tractable, we develop an approximated probability of correct ranking and derive the asymptotic optimality condition based on it. A sequential ranking procedure is then suggested to implement the proposed simulation budget allocation rule. The high efficiency of the proposed simulation procedure is demonstrated via a set of numerical experiments. In addition, useful insights and analysis on characterizing the optimality condition and implementing the efficient budget allocation rule are provided.

Suggested Citation

  • Hui Xiao & Fei Gao & Loo Hay Lee, 2020. "Optimal computing budget allocation for complete ranking with input uncertainty," IISE Transactions, Taylor & Francis Journals, vol. 52(5), pages 489-499, May.
    • Handle: RePEc:taf:uiiexx:v:52:y:2020:i:5:p:489-499
    DOI: 10.1080/24725854.2019.1659524
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    Cited by:

    1. Zhou, Yu & Kou, Gang & Guo, Zhen-Zhu & Xiao, Hui, 2023. "Availability analysis of shared bikes using abnormal trip data," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    2. Hui Xiao & Minhao Cao & Gang Kou & Xiaojun Yuan, 2021. "Optimal element allocation and sequencing of multi-state series systems with two levels of performance sharing," Journal of Risk and Reliability, , vol. 235(2), pages 282-292, April.
    3. Corlu, Canan G. & Akcay, Alp & Xie, Wei, 2020. "Stochastic simulation under input uncertainty: A Review," Operations Research Perspectives, Elsevier, vol. 7(C).
    4. Ding, Yi & Hu, Yishuang & Li, Daqing, 2021. "Redundancy Optimization for Multi-Performance Multi-State Series-Parallel Systems Considering Reliability Requirements," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Qiu, Qingan & Cui, Lirong & Wu, Bei, 2020. "Dynamic mission abort policy for systems operating in a controllable environment with self-healing mechanism," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

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