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Methods for selecting the best system (1991)
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Source Winter Simulation Conference archive
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come table of contents
Washington D.C.
SECTION: Landmark papers from the first 40 years table of contents
Article No. 7  
Year of Publication: 2007
ISBN:1-4244-1306-0
Authors
David Goldsman  Georgia Institute of Technology, Atlanta, Georgia
Barry L. Nelson  The Ohio State University, Columbus, Ohio
Bruce Schmeiser  Purdue University, West Lafayette, Indiana
Sponsors
INFORMS-SIM : Institute for Operations Research and the Management Sciences: Simulation Society
NIST : National Institute of Standards and Technology
(SCS) : The Society for Modeling and Simulation International
ACM/SIGSIM : Association for Computing Machinery: Special Interest Group on Simulation
IIE : Institute of Industrial Engineers
ASA : American Statistical Association
IEEE/SMC : Institute of Electrical and Electronics Engineers: Systems, Man, and Cybernetics Society
Publisher
IEEE Press  Piscataway, NJ, USA
Bibliometrics
Downloads (6 Weeks): 2,   Downloads (12 Months): 17,   Citation Count: 0
Additional Information:

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ABSTRACT

In this tutorial we consider three methods for selecting the best of a set of competing systems: interactive analysis, ranking and selection, and multiple comparisons. We describe each method; discuss assumptions, implementation aspects, advantages, and disadvantages; and demonstrate the use of each method with an airline-reservation-system simulation example.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Bechhofer, R. E., C. Dunnett, D. Goldsman, and M. Hartmann. 1990. A Comparison of the performances of procedures for selecting the normal population having the largest mean when the populations have a common unknown variance. Communications in Statistics---Simulation and Computation B19, 971--1006.
 
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Hsu, J. C. 1984. Ranking and selection and multiple comparisons with the best. In: Design of Experiments: Ranking and Selection, eds. T. J. Santner and A. C. Tamhane, 23--33. New York: Marcel Dekker.
 
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Nelson, B. L. 1992. Statistical analysis of simulation results. In: Handbook of Industrial Engineering, Second Edition, ed. G. Salvendy, in press. New York: John Wiley.
 
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Rinott, Y. 1978. On two-stage selection procedures and related probability inequalities. Communications in Statistics A7, 799--811.
 
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Schmeiser, B. W. 1982. Batch size effects in the analysis of simulation output. Operations Research 30, 556--568.
 
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Schmeiser, B. W. 1990. Simulation experiments. In: Handbook of Operations Research and Management Science, Volume 2: Stochastic Models, eds. D. Heyman and M. Sobel, 295--330. Amsterdam: North Holland.
 
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Schmidt, J. W., and R. E. Taylor. 1970. Simulation and Analysis of Industrial Systems. Homewood, Illinois: Richard D. Irwin.
 
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Wilcox, R. R. 1984. A table for Rinott's selection procedure. Journal of Quality Technology 16, 97--100.
 
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Yang, W., and B. L. Nelson. 1991. Using common random numbers and control variates in multiple-comparison procedures. Operations Research 39, in press.
Collaborative Colleagues:
David Goldsman: colleagues
Barry L. Nelson: colleagues
Bruce Schmeiser: colleagues