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inria-00169080, version 5
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Analysis of a quadratic programming decomposition algorithm
William Hager a1, Guy Bencteux () b2, Eric Cancès c2, Claude Le Bris () c2
(2007)
Icone de paper_INRIA.pdf
We analyze a decomposition algorithm for minimizing a quadratic objective function, separable in x1 and x2, subject to the constraint that x1 and x2 are orthogonal vectors on the unit sphere. Our algorithm consists of a local step where we minimize the objective function in either variable separately, while enforcing the constraints, followed by a global step where we minimize over a subspace generated by solutions to the local subproblems. We establish a local convergence result when the global minimizers nondegenerate. Our analysis employs necessary and sufficient conditions and continuity properties for a global optimum of a quadratic objective function subject to a sphere constraint and a linear constraint. The analysis is connected with a new domain decomposition algorithm for electronic structure calculations.
a –  University of Florida
b –  EDF
c –  Ecole Nationale des Ponts et Chaussées
1 :  Department of Mathematics
University of Florida
2 :  MICMAC (INRIA Rocquencourt)
INRIA – Ecole Nationale des Ponts et Chaussées
Mathématiques/Analyse numérique
RR-6288