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References

The list below includes some links to PostScript files of the most recent versions of the papers for which these links have been given. If you wish to save the PostScript file rather than have it pop up some helper application window (e.g., ghostview), click on the link with the SHIFT key depressed. With the Netscape browser, at least, this will bring up a "Save As" dialog box.

1
A. J. Booker, A. R. Conn, J. E. Dennis, P. D. Frank, D. Serafini, V. Torczon, and M. Trosset.
Multi-level design optimization: A Boeing/IBM/Rice collaborative project. 1996 final report.
Technical Report ISSTECH-96-031, Boeing Information & Support Services, Research & Technology, Technology, P.O. Box 3707, M/S 7L-68, Seattle, WA 98124-2207, December 1996.

2
A. J. Booker, J. E. Dennis, Jr., P. D. Frank, D. B. Serafini, V. Torczon, and M. W. Trosset.
A rigorous framework for optimization of expensive functions by surrogates.
Structural Optimization, Vol. 17, No. 1, February 1999, pp. 1-13.

3
A. R. Conn and Ph. L. Toint.
An algorithm using quadratic interpolation of unconstrained derivative free optimization.
Nonlinear Optimization and Applications, G. Di Pillo and F. Giannessi, editors.
Plenum Publishing, New York, 1996, pp. 27-47.

4
D. D. Cox and S. John.
SDO: a statistical method for global optimization.
Multidisciplinary Design Optimization: State of the Art, N. Alexandrov and M. Y. Hussaini, editors.
SIAM, Philadelphia, 1997.

5
P. D. Frank.
Global modeling for optimization.
SIAG/OPT View-and-News: A Forum for the SIAM Activity Group on Optimization, Vol. 7, 1995, pp. 9--12.

6
R. M. Lewis and V. Torczon.
Pattern search algorithms for bound constrained minimization.
SIAM Journal on Optimization, Vol. 9, No. 4, pp. 1082-1099, 1999.

7
R. M. Lewis and V. Torczon.
Pattern search methods for linearly constrained minimization.
Technical Report 98-3, Institute for Computer Applications in Science and Engineering, Mail Stop 403, NASA Langley Research Center, Hampton, Virginia 23681-0001, January 1998.
To appear in SIAM Journal on Optimization.

8
J. Mockus.
Bayesian Approach to Global Optimization: Theory and Applications.
Kluwer Academic Publishers, Dordrecht, 1989.

9
M. J. D. Powell.
A direct search optimization method that models the objective and constraint functions by linear interpolation.
Advances in Optimization and Numerical Analysis, Proceedings of the 6th Workshop on Optimization and Numerical Analysis, Oaxaca, Mexico, Volume 275.
Kluwer Academic Publishers, Dordrecht, 1994, pp. 51-67.

10
D. B. Serafini.
A Framework for Managing Models in Optimization for Computationally Expensive Functions.
PhD thesis, Department of Computational and Applied Mathematics, Rice University, Houston, TX, 1998.

11
M. W. Trosset and V. Torczon.
Numerical optimization using computer experiments.
Technical Report 97-38, Institute for Computer Applications in Science and Engineering, Mail Stop 403, NASA Langley Research Center, Hampton, Virginia 23681-0001, August 1997.

12
C. F. Van Loan.
Introduction to Scientific Computing: A Matrix-Vector Approach Using Matlab.
Prentice-Hall, Upper Saddle River, NJ, 1997.

13
W. J. Welch and J. Sacks.
A system for quality improvement via computer experiments.
Communications in Statistics--Theory and Methods, 20:477-495, 1991.

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Virginia Torczon
11/2/1999