Selecting the best system: theory and methods

This paper provides an advanced tutorial on the construction of ranking-and-selection procedures for selecting the best simulated system. We emphasize procedures that provide a guaranteed probability of correct selection, and the key theoretical results that are used to derive them.

[1]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[2]  B. Nelson,et al.  Using common random numbers for indifference-zone selection and multiple comparisons in simulation , 1995 .

[3]  R. Wilcox A Table for Rinott's Selection Procedure , 1984 .

[4]  M. Hartmann An improvement on paulson's procedure for selecting the poprlation with the largest mean from k normal populations with a common unknown variance , 1991 .

[5]  Barry L. Nelson,et al.  Using Ranking and Selection to "Clean Up" after Simulation Optimization , 2003, Oper. Res..

[6]  James R. Wilson,et al.  A Multiplicative Decomposition Property of the Screening-and-Selection Procedures of Nelson et al , 2001, Oper. Res..

[7]  E. Dudewicz The heteroscedastic method: fifty+ years of progress 1945–2000, and Professor Minoru Siotani's award-winning contributions , 1996 .

[8]  Chun-Hung Chen,et al.  Computing efforts allocation for ordinal optimization and discrete event simulation , 2000, IEEE Trans. Autom. Control..

[9]  R. Bechhofer A Single-Sample Multiple Decision Procedure for Ranking Means of Normal Populations with known Variances , 1954 .

[10]  Donald L. Iglehart,et al.  Simulation Output Analysis Using Standardized Time Series , 1990, Math. Oper. Res..

[11]  B. Turnbull,et al.  Group Sequential Methods with Applications to Clinical Trials , 1999 .

[12]  S. Gupta On Some Multiple Decision (Selection and Ranking) Rules , 1965 .

[13]  M. Hartmann An improvement on paulson s sequential ranking procedure , 1988 .

[14]  Stephen E. Chick,et al.  New Two-Stage and Sequential Procedures for Selecting the Best Simulated System , 2001, Oper. Res..

[15]  J. Hsu Multiple Comparisons: Theory and Methods , 1996 .

[16]  J. Banks,et al.  Discrete-Event System Simulation , 1995 .

[17]  Seong-Hee Kim,et al.  Comparison with a standard via fully sequential procedures , 2005, TOMC.

[18]  D. Siegmund Sequential Analysis: Tests and Confidence Intervals , 1985 .

[19]  A. Tamhane,et al.  Multiple Comparison Procedures , 1989 .

[20]  A. Tamhane Design and Analysis of Experiments for Statistical Selection, Screening, and Multiple Comparisons , 1995 .

[21]  E. Paulson A Sequential Procedure for Selecting the Population with the Largest Mean from $k$ Normal Populations , 1964 .

[22]  I. Johnstone,et al.  ASYMPTOTICALLY OPTIMAL PROCEDURES FOR SEQUENTIAL ADAPTIVE SELECTION OF THE BEST OF SEVERAL NORMAL MEANS , 1982 .

[23]  B. L. Welch THE SIGNIFICANCE OF THE DIFFERENCE BETWEEN TWO MEANS WHEN THE POPULATION VARIANCES ARE UNEQUAL , 1938 .

[24]  S. Elmaghraby,et al.  A Single-Sample Multiple-Decision Procedure for Selecting the Multinomial Event Which Has the Highest Probability , 1959 .

[25]  D. Slepian The one-sided barrier problem for Gaussian noise , 1962 .

[26]  Barry L. Nelson,et al.  A fully sequential procedure for indifference-zone selection in simulation , 2001, TOMC.

[27]  James R. Wilson,et al.  Restricted Subset Selection Procedures for Simulation , 1989, Oper. Res..

[28]  C. Stein A Two-Sample Test for a Linear Hypothesis Whose Power is Independent of the Variance , 1945 .

[29]  Y. Rinott On two-stage selection procedures and related probability-inequalities , 1978 .

[30]  Julie L. Swann,et al.  Simple Procedures for Selecting the Best Simulated System When the Number of Alternatives is Large , 2001, Oper. Res..

[31]  V. Fabian Note on Anderson's Sequential Procedures with Triangular Boundary , 1974 .

[32]  A. Law,et al.  A procedure for selecting a subset of size m containing the l best of k independent normal populations, with applications to simulation , 1985 .

[33]  J. O. Miller,et al.  Efficient multinomial selection in simulation , 1998 .

[34]  A. Kimball On Dependent Tests of Significance in the Analysis of Variance , 1951 .

[35]  Barry L. Nelson,et al.  Comparisons with a Standard in Simulation Experiments , 2001, Manag. Sci..