Convex quadratic programming with one constraint and bounded variables |
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Authors: | Jean-Pierre Dussault Jacques A Ferland Bernard Lemaire |
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Institution: | (1) Département de mathématiques et d’informatique, Université de Sherbrooke, Canada;(2) Département d’informatique et de recherche opérationnelle, Université de Montréal, Canada;(3) U.E.R. Mathématiques, Université de Montpellier 2, France |
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Abstract: | In this paper we propose an iterative algorithm for solving a convex quadratic program with one equality constraint and bounded
variables. At each iteration, a separable convex quadratic program with the same constraint set is solved. Two variants are
analyzed: one that uses an exact line search, and the other a unit step size. Preliminary testing suggests that this approach
is efficient for problems with diagonally dominant matrices.
This work was supported by a research grant from the France-Quebec exchange program and also by NSERC Grant No. A8312. The
first author was supported by a scholarship from Transport Canada while doing this research. |
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Keywords: | Quadratic programming projection iterative procedure separable programs |
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