A test problem generator for large-scale unconstrained optimization

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A test problem generator for large-scale unconstrained optimization

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ACM Transactions on Mathematical Software (TOMS) archive
Volume 11 , Issue 2 (June 1985) table of contents

Pages: 97 - 102

Year of Publication: 1985

ISSN:0098-3500

Authors

R. S. Dembo	School of Organization and Management, Yale University, Box 1A, New Haven, CT
T. Steihaug	Statoil, Forus, P.O. Box 300, 4001 Stawanger, Norway

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ACM New York, NY, USA

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ABSTRACT

A test problem generator for large-scale unconstrained optimization is described. It permits the generation of a poorly or well-conditioned problems of arbitrary size, derived from nonlinear network flow models. An eigenvalue analysis provides bounds on the condition number of the Hessian of the objective function and an example of an efficient preconditioner, using these bounds, is outlined.

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	COLVILLE, A.R. A comparative study on nonlinear programming codes. In Proceedings of the Princeton Symposium on Mathematical Programming, H. W. Kuhn, Ed. Princeton University Press, Princeton, N.J., 1970, pp. 487-501.
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	3	DEMnO, R. S., AND STEIHAUG, T. Truncated-Newton algorithms for large-scale unconstrained optimization. Math. Program. 26 (1983), 190-212.
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	7	TOINT, P.L. Some numerical results using a sparse matrix updating in unconstrained optimization. Math. Comput. 32 (1978), 839-851.