Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-04T19:45:51.316Z Has data issue: false hasContentIssue false

Sufficient global optimality conditions for multi-extremal smooth minimisation problems with bounds and linear matrix inequality constraints

Published online by Cambridge University Press:  17 February 2009

N. Q. Huy
Affiliation:
Department of Mathematics, Hanoi Pedagogical UniversityNo. 2, Vinh Phuc, Vietnam.
V. Jeyakumar
Affiliation:
Department of Applied Mathematics, University of New South Wales, Sydney NSW 2052, Australia; e-mail: [email protected].
G. M. Lee
Affiliation:
Department of Applied Mathematics, Pukyong National University, Pusan 608–737, Korea; e-mail: [email protected].
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In this paper, we present sufficient conditions for global optimality of a general nonconvex smooth minimisation model problem involving linear matrix inequality constraints with bounds on the variables. The linear matrix inequality constraints are also known as “semidefinite” constraints which arise in many applications, especially in control system analysis and design. Due to the presence of nonconvex objective functions such minimisation problems generally have many local minimisers which are not global minimisers. We develop conditions for identifying global minimisers of the model problem by first constructing a (weighted sum of squares) quadratic underestimator for the twice continuously differentiable objective function of the minimisation problem and then by characterising global minimisers of the easily tractable underestimator over the same feasible region of the original problem. We apply the results to obtain global optimality conditions for optinusation problems with discrete constraints.

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 2006

References

[1]Akrotirianakis, I. G. and Floudas, C. A., “Computational experience with a new class of convex underestimators: Box-constrained NLP problems”, J. Global Optim. 29 (2004) 249264.CrossRefGoogle Scholar
[2]Beck, A. and Teboulle, M., “Global optimality conditions for quadratic optimization problems with binary constraints”, SIAM J. Optim. 11 (2000) 179188.CrossRefGoogle Scholar
[3]Ben-Tal, A. and Nemirovski, A., Lectures on Modern Convex Optimization: Analysis, Algorithms and Engineering Applications (SIAM-MPS, Philadelphia, 2000).Google Scholar
[4]Dahl, G., “A note on diagonally dominant matrices”, Linear Algebra Appl. 317 (2000) 217224.CrossRefGoogle Scholar
[5]Floudas, C. A. and Visweswaran, V., “Quadratic optimization”, in Handbook of Global Optimization (eds. Horst, R. and Pardalos, P. M.), (Kluwer Academic Publishers, Dordrecht, 1995) 217269.CrossRefGoogle Scholar
[6]Helmberg, C., “Semidefinite programming”, European J. Oper. Res. 137 (2002) 461482.CrossRefGoogle Scholar
[7]Hiriart-Urruty, J. B., “Conditions for global optimality 2”, J. Global Optim. 13 (1998) 349367.CrossRefGoogle Scholar
[8]Hiriart-Urruty, J. B., “Global optimality conditions in maximizing a convex quadratic function under convex quadratic constraints”, J. Global Optim. 21 (2001) 445455.CrossRefGoogle Scholar
[9]Jeyakumar, V., Rubinov, A. M. and Wu, Z. Y., “Sufficient global optimality conditions for nonconvex quadratic minimization problems with box constraints”, Applied Mathematics Research Report AMRO5/20, University of New South Wales, Australia, to appear in J. Global Optim.Google Scholar
[10]Pinar, M. C., “Sufficient global optimality conditions for bivalent quadratic optimization”, J. Optim. Theory Appl. 122 (2004) 433440.CrossRefGoogle Scholar
[11]Todd, M. J., “Semidefinite optimization”, Acta Numerica 10 (2001) 515560.CrossRefGoogle Scholar
[12]Wolkowicz, H., Saigal, R. and Vandenberghe, L., Handbook of semidefinite programming, International Series in Operations Research and Management Science 27 (Kluwer Academic Publishers, Dordrecht, 2000).CrossRefGoogle Scholar