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.
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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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Dussault, JP., Ferland, J.A. & Lemaire, B. Convex quadratic programming with one constraint and bounded variables. Mathematical Programming 36, 90–104 (1986). https://doi.org/10.1007/BF02591992
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DOI: https://doi.org/10.1007/BF02591992