A fully sequential procedure for indifference-zone selection in simulation

By Seong-Hee Kim, Barry L. Nelson. TOMC, 2001

455 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0b1d2c5cd4be620b078123f555355efa09f8b535

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In Computer Networks and Communications

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

A bilevel optimization approach to automated parameter tuning (2014, background): “There also exist a number of screening methods [23, 7] that attempt to select the best parameter vector with as few simulations as possible.”
Simple Procedures for Selecting the Best Simulated System When the Number of Alternatives is Large (2001, methodology): “Examples include the restricted subset-selection procedures (RSSPs)2 of Koenig and Law (1985), Santner (1975), and Sullivan and Wilson (1989); and the IZ selection procedure of Dudewicz and Dalal (1975).”
A Knowledge-Gradient Policy for Sequential Information Collection (2008, background): “We do not review this literature in detail, but state only that an overview may be found in [1] and that a more recent policy which performs quite well in the multistage setting with normal rewards is given in [23], [22].”
Parameter tuning for configuring and analyzing evolutionary algorithms (2011, background): “Interactive Analysis (IA) [47], Ranking and Selection (R&S) [48], Multiple Comparison Procedures (MPC) [49] and Fully sequential indifference-zone selection procedure(FSP) [50] are the four main approaches from this field [51].”
Selecting the best system when systems are revealed sequentially (2007, methodology): “Among the frequentist procedures, Kim and Nelson (2001) first introduce a fully sequential procedure to solve simulation selection problems.”
The Knowledge-Gradient Policy for Correlated Normal Beliefs (2009, methodology): “Within this literature, the techniques that most successfully exploit dependence are variancereduction techniques for simulation (Law and Kelton 2000), which include control variates (Nelson and Staum 2006) and common random numbers (Kim and Nelson 2001).”
Fully sequential procedures for comparing constrained systems via simulation (2010, methodology): “We useAlgorithmF as P ′ I and theKN procedure due to Kim and Nelson [18] asP ′ II.”
Simulation optimization for an emergency department healthcare unit in Kuwait (2009, methodology): “For more details on those procedures, see Yan and Mukai (1992), Andradottir (1995, 1996), Alrefaei and Andradottir (1999), Ahmed et al. (1998), Alkhamis et al. (1999), Ahmed and Alkhamis (2002), Alkhamis and Ahmed (2004), Kim and Nelson (2001), and Boesel et al. (2003).”