Constraint Qualifications Characterizing Lagrangian Duality in Convex Optimization

Abstract In convex optimization, a constraint qualification (CQ) is an essential ingredient for the elegant and powerful duality theory. Various constraint qualifications which are sufficient for the Lagrangian duality have been given in the literature. In this paper, we present constraint qualifications which characterize completely the Lagrangian duality.

[1]  V. Jeyakumar,et al.  A note on strong duality in convex semidefinite optimization: necessary and sufficient conditions , 2007, Optim. Lett..

[2]  Henry Wolkowicz,et al.  Strong Duality for Semidefinite Programming , 1997, SIAM J. Optim..

[3]  Heinz H. Bauschke,et al.  Strong conical hull intersection property, bounded linear regularity, Jameson’s property (G), and error bounds in convex optimization , 1999, Math. Program..

[4]  Vaithilingam Jeyakumar,et al.  Inequality systems and global optimization , 1996 .

[5]  Jonathan M. Borwein,et al.  Partially finite convex programming, Part I: Quasi relative interiors and duality theory , 1992, Math. Program..

[6]  Henry Wolkowicz,et al.  Generalizations of Slater's constraint qualification for infinite convex programs , 1992, Math. Program..

[7]  V. Jeyakumar The strong conical hull intersection property for convex programming , 2006, Math. Program..

[8]  Vaithilingam Jeyakumar,et al.  Limiting epsilon-subgradient characterizations of constrained best approximation , 2005, J. Approx. Theory.

[9]  J. Hiriart-Urruty,et al.  Convex analysis and minimization algorithms , 1993 .

[10]  G. A. Garreau,et al.  Mathematical Programming and Control Theory , 1979, Mathematical Gazette.

[11]  Gert Wanka,et al.  An alternative formulation for a new closed cone constraint qualification , 2006 .

[12]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[13]  Vaithilingam Jeyakumar,et al.  A simple closure condition for the normal cone intersection formula , 2004 .

[14]  C. Zălinescu Convex analysis in general vector spaces , 2002 .