Selecting the best system: Theory and methods

Winter Simulation Conference Proceedings

Volumn 1, Issue , 2003, Pages 101-112

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

^a Georgia Institute of Technology   (United States)

^b Northwestern University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; PROBABILITY; RANDOM PROCESSES; SET THEORY; STATISTICAL METHODS; VECTORS;

MULTIPLE COMPARISON PROCEDURES (MCP); SUBSET SELECTION FORMULATION;

COMPUTER SYSTEMS;

EID: 1642437893     PISSN: 02750708     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (42)

1. Banerjee, S. 1961. On confidence interval for two-means problem based on separate estimates of variances and tabulated values of t-table. Sankkyā A23:359-378.
2. Banks, J., J. S. Carson, B. L. Nelson, and D. Nicol. 2001. Discrete-Event System Simulation. Upper Saddle River, NJ: Prentice Hall.
3. Bechhofer, R. E. 1954. A single-sample multiple decision procedure for ranking means of normal populations with known variances. Annals of Mathematical Statistics 25:16-39.
4. Bechhofer, R. E., S. Elmaghraby, and N. Morse. 1959. A single-sample multiple-decision procedure for selecting the multinomial event which has the highest probability. Annals of Mathematical Statistics 30:102-119.
5. Bechhofer, R. E., T. J. Santner, and D. Goldsman. 1995. Design and Analysis of Experiments for Statistical Selection, Screening and Multiple Comparisons. New York: John Wiley & Sons.
6. Boesel, J., B. L. Nelson, and S.-H. Kim. 2003. Using ranking and selection to "clean up" after simulation optimization. To appear in Operations Research.
7. Chen, H. C., C. H. Chen, and E. Yücesan. 2000. Computing efforts allocation for ordinal optimization and discrete event simulation. IEEE Transactions on Automatic Control 45:960-964
8. Chick, S., and K. Inoue. 2001. New two-stage and sequential procedures for selecting the best simulated system. Operations Research 49:1609-1624.
9. Dudewicz, E. J. 1995. The heteroscedastic method: Fifty+ years of progress 1945-2000, and professor Minoru Siotani's award-winning contributions. American Journal of Mathematical and Management Sciences 15:179-197.
10. Fabian, V. 1974. Note on Anderson's sequential procedures with triangular boundary. Annals of Statistics 2:170-176.
11. Glynn, P. W., and D. L. Iglehart. 1990. Simulation output analysis using standardized time series. Mathematics of Operations Research 15:1-16.
12. Goldsman, D., and B. L. Nelson. 1998. Comparing systems via simulation. In Handbook of Simulation, ed. J. Banks, 273-306. New York: John Wiley.
13. Gupta, S. S. 1956. On a decision rule for a problem in ranking means. Doctoral dissertation, Institute of Statistics, Univ. of North Carolina, Chapel Hill, NC.
14. Gupta, S. S. 1965. On some multiple decision (ranking and selection) rules. Technometrics 7:225-245.
15. Hartmann, M. 1988. An improvement on Paulson's sequential ranking procedure. Sequential Analysis 7:363-372.
16. Hartmann, M. 1991. 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 10:1-16.
17. Hochberg, Y., and A. C. Tamhane. 1987. Multiple Comparison Procedures. New York: John Wiley.
18. Hong, L. J., and B. L. Nelson. 2003. The tradeoff between sampling and switching: New sequential procedures for indifference-zone selection. Technical Report, Dept. of IEMS, Northwestern Univ., Evanston, IL.
19. Hsu, J. C. 1996. Multiple Comparisons: Theory and Methods, New York: Chapman & Hall.
20. Jennison, C., I. M. Johnstone, and B. W. Turnbull. 1980. Asymptotically optimal procedures for sequential adaptive selection of the best of several normal means. Technical Report, Dept. of ORIE, Cornell Univ., Ithaca, NY.
21. Jennison, C., I. M. Johnstone, and B. W. Turnbull. 1982. Asymptotically optimal procedures for sequential adaptive selection of the best of several normal means. In Statistical Decision Theory and Related Topics III, Vol. 2, ed. S. S. Gupta and J. O. Berger, 55-86. New York: Academic Press.
22. Jennison, C., and B. W. Turnbull. 2000. Group Sequential Methods with Applications to Clinical Trials. New York: Chapman & Hall.
23. Koenig, L. W., and A. M. Law. 1985. 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 614:719-734.
24. Kim, S.-H. 2002. Comparison with a standard via fully sequential procedures. Technical Report, School of ISyE, Georgia Tech, Atlanta, GA.
25. Kim, S.-H., and B. L. Nelson. 2001. A fully sequential procedure for indifference-zone selection in simulation. ACM TOMACS 11:251-273.
26. Kim, S.-H., and B. L. Nelson. 2003. On the asymptotic validity of fully sequential selection procedures for steady-state simulation. Technical Report, Dept. of IEMS, Northwestern Univ., Evanston, IL.
27. Kimball, A. W. 1951. On dependent tests of significance in the analysis of variance. Annals of Mathematical Statistics 22:600-602.
28. Law, A. M., and W. D. Kelton. 2000. Simulation modeling and analysis, 3d ed. New York: McGraw-Hill.
29. Miller, J. O., B. L. Nelson, and C. H. Reilly. 1998. Efficient multinomial selection in simulation. Naval Research Logistics 45:459-482.
30. Nelson, B. L., and D. Goldsman. 2001. Comparisons with a standard in simulation experiments, Management Science 47:449-463.
31. Nelson, B. L., and F. J. Matejcik. 1995. Using common random numbers for indifference-zone selection and multiple comparisons in simulation. Management Science 41:1935-1945
32. Nelson, B. L., J. Swann, D. Goldsman, and W.-M. T. Song. 2001. Simple procedures for selecting the best system when the number of alternatives is large. Operations Research 49:950-963.
33. Paulson, E. 1964. A sequential procedure for selecting the population with the largest mean from k normal populations. Annals of Mathematical Statistics 35:174-180.
34. Rinott, Y. 1978. On two-stage selection procedures and related probability-inequalities. Communications in Statistics - Theory and Methods A7:799-811.
35. Siegmund, D. 1985. Sequential Analysis: Tests and Confidence Intervals. New York: Springer-Verlag.
36. Slepian, D. 1962. The one-sided barrier problem for Gaussian noise. Bell Systems Technical Journal 41:463-501.
37. Stein, C. 1945. A two-sample test for a linear hypothesis whose power is independent of the variance. Annals of Mathematical Statistics 16:243-258.
38. Sullivan, D. W., and J. R. Wilson. 1989. Restricted subset selection for simulation. Operations Research 37:52-71.
39. Wald, A. 1947. Sequential Analysis. New York: John Wiley.
40. Welch, B. L. 1938. The significance of the difference between two means when the population variances are unequal. Biometrika 25:350-362.
41. Wilcox, R. R. 1984. A table for Rinott's selection procedure. Journal of Quality Technology 16:97-100.
42. Wilson, J. R. 2001. A multiplicative decomposition property of the screening-and-selection procedures of Nelson et al. Operations Research 49:964-966.