排序与选择：一个新的视角
Review on Ranking and Selection: A New Perspective
摘要：
本文简要回顾了排序与选择（R&S）在过去70年中的发展，特别是近20年来的理论成果和实际应用。与Kim和Nelson（2006 b）和Chick（2006）在其综述文章中采用的频率论和贝叶斯分类不同，我们将现有的R&S程序分为固定精度和固定预算程序，如Hunter和Nelson（2017）。我们表明，这两类程序本质上不同的基本方法的配方，即，它们分别建立在假设检验和动态编程的基础上。鉴于这种变化，我们详细回顾了文献中的一些众所周知的程序，并展示了它们如何适合这两种配方。此外，我们还讨论了R&S程序在解决各种实际问题中的应用，并提出了我们认为该领域中重要的研究问题。
英文摘要：
In 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 last 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.
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