Review on ranking and selection: A new perspective

Author:

Hong L. Jeff,Fan Weiwei,Luo Jun

Abstract

AbstractIn this paper, we briefly review the development of ranking and selection (R&S) in the past 70 years, especially the theoretical achievements and practical applications in the past 20 years. Different from the frequentist and Bayesian classifications adopted by Kim and Nelson (2006b) and Chick (2006) in their review articles, we categorize existing R&S procedures into fixed-precision and fixed-budget procedures, as in Hunter and Nelson (2017). We show that these two categories of procedures essentially differ in the underlying methodological formulations, i.e., they are built on hypothesis testing and dynamic programming, respectively. In light of this variation, we review in detail some well-known procedures in the literature and show how they fit into these two formulations. In addition, we discuss the use of R&S procedures in solving various practical problems and propose what we think are the important research questions in the field.

Publisher

Springer Science and Business Media LLC

Reference109 articles.

1. Andradóttir S, Kim S H (2010). Fully sequential procedures for comparing constrained systems via simulation. Naval Research Logistics, 57(5): 403–421

2. Applegate E A, Feldman G, Hunter S R, Pasupathy R (2020). Multi-objective ranking and selection: Optimal sampling laws and tractable approximations via SCORE. Journal of Simulation, 14(1): 21–40

3. Banerjee S (1961). On confidence interval for two-means problem based on separate estimates of variances and tabulated values of t-table. Sankhya Series A, 23(4): 359–378

4. Batur D, Choobineh F (2012). Stochastic dominance based comparison for system selection. European Journal of Operational Research, 220(3): 661–672

5. Batur D, Wang L, Choobineh F F (2018). Methods for systems selection based on sequential mean-variance analysis. INFORMS Journal on Computing, 30(4): 724–738

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