Non-convex quadratic minimization problems with quadratic constraints: global optimality conditions

In this paper, we first examine how global optimality of non-convex constrained optimization problems is related to Lagrange multiplier conditions. We then establish Lagrange multiplier conditions for global optimality of general quadratic minimization problems with quadratic constraints. We also ob...

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Veröffentlicht in:	Mathematical programming Jg. 110; H. 3; S. 521 - 541
Hauptverfasser:	Jeyakumar, V., Rubinov, A. M., Wu, Z. Y.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Heidelberg Springer 01.09.2007 Springer Nature B.V
Schlagworte:	Applied mathematics Applied sciences Constraints Convex analysis Exact sciences and technology Information technology Lagrange multiplier Mathematical functions Mathematical programming Operational research and scientific management Operational research. Management science Optimization Quadratic programming Studies Non convex programming Quadratic inequality constraints Non-convex quadratic minimization Constraint satisfaction Minimization Global optimum Quadratic programming Binary constraints Convex programming Constrained optimization Lagrange multiplier Global optimality conditions Least squares method Lagrange multipliers Inequality constraint Optimality condition Optimality criterion Ellipsoid Non convex analysis Mathematical programming
ISSN:	0025-5610, 1436-4646
Online-Zugang:	Volltext
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