On the duality of quadratic minimization problems using pseudo inverses
Subject Areas : Numerical analysis
D. Pappas
1
(Department of Statistics, Athens University of Economics and Business, 76 Patission Str 10434, Athens, Greece)
G. Domazakis
2
(Department of Mathematics, School of Applied Mathematics and Physical Sciences, National Technical University of Athens, Iroon Polytexneiou 9, 15780 Zografou, Athens, Greece)
Keywords: Moore-Penrose inverse, Lagrange multipliers, constrained optimization, general normal equation, duality principle, KKT conditions,
Abstract :
In this paper we consider the minimization of a positive semidefinite quadratic form, having a singular corresponding matrix $H$. We state the dual formulation of the original problem and treat both problems only using the vectors $x \in \mathcal{N}(H)^\perp$ instead of the classical approach of convex optimization techniques such as the null space method. Given this approach and based on the strong duality principle, we provide a closed formula for the calculation of the Lagrange multipliers $\\lambda$ in the cases when (i) the constraint equation is consistent and (ii) the constraint equation is inconsistent, using the general normal equation. In both cases the Moore-Penrose inverse will be used to determine a unique solution of the problems. In addition, in the case of a consistent constraint equation, we also give sufficient conditions for our solution to exist using the well known KKT conditions.
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