Chapter 17 Selecting the Best System

Handbooks in Operations Research and Management Science

Volumn 13, Issue C, 2006, Pages 501-534

  Kim, Seong Hee ^a,b   Nelson, Barry L ^a,b  

^a Georgia Institute of Technology   (United States)

^b Northwestern University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 77950495137     PISSN: 09270507     EISSN: None     Source Type: Book Series    
DOI: 10.1016/S0927-0507(06)13017-0     Document Type: Review

References (63)

1. Banerjee S. On confidence interval for two-means problem based on separate estimates of variances and tabulated values of t-table. Sankhyā A 23 (1961) 359-378
2. Banks J., Carson J.S., Nelson B.L., and Nicol D. Discrete-Event System Simulation. 4th edition (2005), Prentice Hall, Upper Saddle River, NJ
3. Bechhofer R.E. A single-sample multiple decision procedure for ranking means of normal populations with known variances. Annals of Mathematical Statistics 25 (1954) 16-39
4. Bechhofer R.E., and Goldsman D. Truncation of the Bechhofer-Kiefer-Sobel sequential procedure for selecting the multinomial event which has the largest probability, II: Extended tables and an improved procedure. Communications in Statistics - Simulation and Computation B 15 (1986) 829-851
5. Bechhofer R.E., and Turnbull B.W. Two (k + 1)-decision selection procedures for comparing k normal means with a specified standard. Journal of the American Statistical Association 73 (1978) 385-392
6. Bechhofer R.E., Elmaghraby S., and Morse N. A single-sample multiple-decision procedure for selecting the multinomial event which has the highest probability. Annals of Mathematical Statistics 30 (1959) 102-119
7. Bechhofer R.E., Santner T.J., and Goldsman D. Design and Analysis of Experiments for Statistical Selection, Screening and Multiple Comparisons (1995), Wiley, New York
8. Boesel J., Nelson B.L., and Kim S.-H. Using ranking and selection to "clean up" after simulation optimization. Operations Research 51 (2003) 814-825
9. Chen H.C., Chen C.H., and Yücesan E. Computing efforts allocation for ordinal optimization and discrete event simulation. IEEE Transactions on Automatic Control 45 (2000) 960-964
10. Chick S., and Inoue K. New two-stage and sequential procedures for selecting the best simulated system. Operations Research 49 (2001) 1609-1624
11. Dalal S.R., and Hall W.J. Most economical robust selection procedures for location parameters. The Annals of Statistics 7 (1977) 1321-1328
12. Damerdji H., and Nakayama M.K. Two-stage multiple-comparison procedures for steady-state simulation. ACM TOMACS 9 (1999) 1-30
13. Damerdji H., Glynn P.W., Nakayama M.K., and Wilson J.R. Selecting the best system in transient simulations with variances known. In: Charnes J.M., Morrice D.J., Brunner D.T., and Swain J.J. (Eds). Proceedings of the 1996 Winter Simulation Conference (1996), IEEE Press, Piscataway, NJ 281-286
14. Dudewicz E.J. An approximation to the sample size in selection problems. Annals of Mathematical Statistics 40 (1969) 492-497
15. Dudewicz E.J. The heteroscedastic method: Fifty+ years of progress 1945-2000, and professor Minoru Siotani's award-winning contributions. American Journal of Mathematical and Management Sciences 15 (1995) 179-197
16. Fabian V. Note on Anderson's sequential procedures with triangular boundary. The Annals of Statistics 2 (1974) 170-176
17. Glynn P.W., and Iglehart D.L. Simulation output analysis using standardized time series. Mathematics of Operations Research 15 (1990) 1-16
18. Goldsman D. A multinomial ranking and selection procedure: Simulation and applications. In: Shepard S., Pooch U.W., and Pegden C.D. (Eds). Proceedings of the 1984 Winter Simulation Conference (1984), IEEE Press, Piscataway, NJ 259-264
19. Goldsman D. On selecting the best of K systems: An expository survey of indifference-zone multinomial procedures. In: Shepard S., Pooch U.W., and Pegden C.D. (Eds). Proceedings of the 1984 Winter Simulation Conference (1984), IEEE Press, Piscataway, NJ 107-112
20. Goldsman D., and Nelson B.L. Comparing systems via simulation. In: Banks J. (Ed). Handbook of Simulation (1998), Wiley, New York 273-306
21. Goldsman D., Kim S.-H., Marshall W., and Nelson B.L. Ranking and selection procedures for steady-state simulation: Perspectives and procedures. INFORMS Journal on Computing 14 (2001) 2-19
22. Gupta, S.S. (1956). On a decision rule for a problem in ranking means. Doctoral dissertation, Institute of Statistics, University of North Carolina, Chapel Hill, NC
23. Gupta S.S. On some multiple decision (ranking and selection) rules. Technometrics 7 (1965) 225-245
24. Hartmann M. An improvement on Paulson's sequential ranking procedure. Sequential Analysis 7 (1988) 363-372
25. Hartmann M. An improvement on Paulson's procedure for selecting the population with the largest mean from k normal populations with a common unknown variance. Sequential Analysis 10 (1991) 1-16
26. Hochberg Y., and Tamhane A.C. Multiple Comparison Procedures (1987), Wiley, New York
27. Hong L.J., and Nelson B.L. The tradeoff between sampling and switching: New sequential procedures for indifference-zone selection. IIE Transactions 37 (2005) 623-634
28. Hsu J.C. Multiple Comparisons: Theory and Methods (1996), Chapman and Hall, New York
29. Jennison C., and Turnbull B.W. Group Sequential Methods with Applications to Clinical Trials (2000), Chapman and Hall, New York
30. Jennison, C., Johnstone, I.M., Turnbull, B.W. (1980). Asymptotically optimal procedures for sequential adaptive selection of the best of several normal means. Technical report, Department of ORIE, Cornell University, Ithaca, NY
31. Jennison C., Johnstone I.M., and Turnbull B.W. Asymptotically optimal procedures for sequential adaptive selection of the best of several normal means. In: Gupta S.S., and Berger J.O. (Eds). Statistical Decision Theory and Related Topics III vol. 2 (1982), Academic Press, New York 55-86
32. Koenig L.W., and Law A.M. A procedure for selecting a subset of size m containing the ℓ best of k independent normal populations, with applications to simulation. Communications in Statistics - Simulation and Computation B 14 (1985) 719-734
33. Kim S.-H. Comparison with a standard via fully sequential procedures. ACM TOMACS 15 (2005) 155-174
34. Kim S.-H., and Nelson B.L. A fully sequential procedure for indifference-zone selection in simulation. ACM TOMACS 11 (2001) 251-273
35. Kim, S.-H., Nelson, B.L. (2006). On the asymptotic validity of fully sequential selection procedures for steady-state simulation, Operations Research, in press
36. Kimball A.W. On dependent tests of significance in the analysis of variance. Annals of Mathematical Statistics 22 (1951) 600-602
37. Law A.M., and Kelton W.D. Simulation Modeling and Analysis. 3rd edition (2000), McGraw-Hill, New York
38. Lehmann E.L. Elements of Large-Sample Theory (1999), Springer-Verlag, New York
39. Mata F. Common random numbers and multinomial selection. Computers and Industrial Engineering 25 (1993) 33-36
40. Miller J.O., and Bauer K.W. How common random numbers affect multinomial selection. In: Andradóttir S., Healy K.J., Withers D.H., and Nelson B.L. (Eds). Proceedings of the 1997 Winter Simulation Conference (1997), IEEE Press, Piscataway, NJ 342-347
41. Miller J.O., Nelson B.L., and Reilly C.H. Efficient multinomial selection in simulation. Naval Research Logistics 45 (1998) 459-482
42. Mukhopadhyay N., and Solanky T.K.S. Multistage Selection and Ranking Procedures: Second-Order Asymptotics (1994), Dekker, New York
43. Nelson B.L., and Goldsman D. Comparisons with a standard in simulation experiments. Management Science 47 (2001) 449-463
44. Nelson B.L., and Matejcik F.J. Using common random numbers for indifference-zone selection and multiple comparisons in simulation. Management Science 41 (1995) 1935-1945
45. Nelson B.L., Swann J., Goldsman D., and Song W.-M.T. Simple procedures for selecting the best system when the number of alternatives is large. Operations Research 49 (2001) 950-963
46. Paulson E. On the comparison of several experimental categories with a control. Annals of Mathematical Statistics 23 (1952) 239-246
47. Paulson E. A sequential procedure for selecting the population with the largest mean from k normal populations. Annals of Mathematical Statistics 35 (1964) 174-180
48. Perng S.K. A comparison of the asymptotic expected sample sizes of two sequential procedures for ranking problem. Annals of Mathematical Statistics 40 (1969) 2198-2202
49. Pichitlamken J., and Nelson B.L. Selection-of-the-best procedures for optimization via simulation. Proceedings of the 2001 Winter Simulation Conference (2001), IEEE Press, Piscataway, NJ 401-407
50. Rinott Y. On two-stage selection procedures and related probability-inequalities. Communications in Statistics - Theory and Methods A 7 (1978) 799-811
51. Robbins H., Sobel M., and Starr N. A sequential procedure for selecting the largest of k means. Annals of Mathematical Statistics 39 (1968) 88-92
52. Ross S.M. Introduction to Probability Models. 7th edition (2000), Academic Press, New York
53. Siegmund D. Sequential Analysis: Tests and Confidence Intervals (1985), Springer-Verlag, New York
54. Slepian D. The one-sided barrier problem for Gaussian noise. Bell Systems Technical Journal 41 (1962) 463-501
55. Smith, M.J. (1995). Ranking and selection: Open sequential procedures for Bernoulli populations. Unpublished MS thesis, School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA
56. Stein C. A two-sample test for a linear hypothesis whose power is independent of the variance. Annals of Mathematical Statistics 16 (1945) 243-258
57. Sullivan D.W., and Wilson J.R. Restricted subset selection for simulation. Operations Research 37 (1989) 52-71
58. Tamhane A.C. Selecting the better Bernoulli treatment using a matched samples design. Journal of the Royal Statistical Society B 42 (1980) 26-30
59. Tamhane A.C. Some sequential procedures for selecting the better Bernoulli treatment using a matched samples design. Journal of the American Statistical Association 80 (1985) 455-460
60. Wald A. Sequential Analysis (1947), Wiley, New York
61. Welch B.L. The significance of the difference between two means when the population variances are unequal. Biometrika 25 (1938) 350-362
62. Wilcox R.R. A table for Rinott's selection procedure. Journal of Quality Technology 16 (1984) 97-100
63. Wilson J.R. A multiplicative decomposition property of the screening-and-selection procedures of Nelson et al. Operations Research 49 (2001) 964-966