Using central composite designs in simulation experiments

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Using central composite designs in simulation experiments

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Winter Simulation Conference archive
Proceedings of the 24th conference on Winter simulation table of contents

Arlington, Virginia, United States

Pages: 529 - 538

Year of Publication: 1992

ISBN:0-7803-0798-4

Author

Jeffrey D. Tew

Sponsors

ASA : American Statistical Association
NIST : National Institue of Standards & Technology
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
ORSA : Operations Research Society of America
SIGSIM: ACM Special Interest Group on Simulation and Modeling
TIMS :
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 12, Downloads (12 Months): 47, Citation Count: 6

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references cited by index terms collaborative colleagues

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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.

	1	Anderson, V. L., and R. A. McLean. 1974. Design of experiments: a realzstic approach. New York: Marcel Dekker.
	2	George E P Box , Norman R Draper, Empirical model-building and response surface, John Wiley & Sons, Inc., New York, NY, 1986
	3	Paul Bratley , Bennett L. Fox , Linus E. Schrage, A guide to simulation (2nd ed.), Springer-Verlag New York, Inc., New York, NY, 1987
	4	Crenshaw, M. D. and J. D. Tew. 1992. A study on the effects that an absence of a pure-error component has in multipopulation simulation experiments. Navel Research Logistics, (to appear).
	5	Joshi, S. and J. D. Tew. 1991. Statistical analysis and validation procedures under the common random number correlation-induction strategy for multipopulation simulation experiments. (submitted).
	6	Averill M. Law , W. David Kelton, Simulation Modeling and Analysis, McGraw-Hill Higher Education, 1997
	7	Mihram, G. A. 1974. Blocking in similar experimental designs. Journal of Slalzstical Compulalzon and Simulatzon 3:29-32.
	8	Myers, R. H. 1976. Response surface methodology. Ann Arbor: Edwards Brothers.
	9	A. Nozari , S. F. Arnold , C. D. Pegden, Statistical analysis for use with the Schruben and Margolin correlation induction strategy, Operations Research, v.35 n.1, p.127-139, Jan.-Feb. 1987 [doi>10.1051/ro:2001107]
	10	A. Alan Pritsker, Introduction to Simulation and SLAM II (3rd ed.), John Wiley & Sons, Inc., New York, NY, 1986
	11	Schruben, L. W. 1979. Designing correlation induction strategies for simulation experiments. In Current zssues in computer s~mulatzon, ed. N. R. Adam and A. Dogramaci, 235-256. New York: Academic Press.
	12	Schruben, L. W., and B. It. Margolin. 1978. Pseudorandom number assignment in statistically designed simulation and distribution sampling experiments. Journal of the Amertcan Staltstzcal Association 73:504-525.
	13	Tew, J. D. 1986. Metamodel estimation under correlation methods for simulation experiments. Ph.D. dissertaion, School of Industrial Engineering, Purdue University, West Lafayette, indiana.
	14	Tew, J. D. 1991. Correlated replicates designs for first-order metamodel estimation in simulation experiments. Tansactions of The Society For Computer Co~mulat~on 8:218-245.
	15	Tew, J. D. 1992. A study of two correlation-induction techniques for fitting a second-order metamodel in simulation experiments. (submitted).
	16	Jeffrey D. Tew , James R. Wilson, Metamodel estimation using integrated correlation methods, Proceedings of the 19th conference on Winter simulation, p.409-418, December 14-16, 1987, Atlanta, Georgia, United States [doi>10.1145/318371.318621]
	17	Jeffrey D. Tew , James R. Wilson, Validation of simulation analysis methods for the Schruben-Margolin correlation-induction strategy, Operations Research, v.40 n.1, p.87-103, Jan.–Feb. 1992 [doi>10.1287/opre.40.1.87]
	18	Tew, J. D., and J. R. Wilson. 1992b. Estimating simulation metamodels using combined correlationbased variance reduction techniques, lie Transaclzons, (to appear).

CITED BY 6

	Phillip A Farrington , James J. Swain, Design of simulation experiments with manufacturing applications, Proceedings of the 25th conference on Winter simulation, p.69-75, December 12-15, 1993, Los Angeles, California, United States
	Joan M. Donohue, The use of variance reduction techniques in the estimation of simulation metamodels, Proceedings of the 27th conference on Winter simulation, p.194-200, December 03-06, 1995, Arlington, Virginia, United States
	Susan M. Sanchez, Design of experiments: robust design: seeking the best of all possible worlds, Proceedings of the 32nd conference on Winter simulation, December 10-13, 2000, Orlando, Florida
	James J. Swain , Phillip A. Farrington, Designing simulation experiments for evaluating manufacturing systems, Proceedings of the 26th conference on Winter simulation, p.69-76, December 11-14, 1994, Orlando, Florida, United States
	Joan M. Donohue, Experimental designs for simulation, Proceedings of the 26th conference on Winter simulation, p.200-206, December 11-14, 1994, Orlando, Florida, United States
	Susan M. Sanchez, A robust design tutorial, Proceedings of the 26th conference on Winter simulation, p.106-113, December 11-14, 1994, Orlando, Florida, United States