Presolving a Convex Quadratic Minimization Problem
DOI:
https://doi.org/10.19139/soic-2310-5070-4658Keywords:
Presolving, Variable reduction, Convex quadratic problem, Equality and box constraintsAbstract
In this work, we consider a convex quadratic minimization problem with one linear equality and box constraints.The goal is to find certain indices active at the optimum in order to fix the corresponding variables in advance. We alsolook for other variables whose corresponding components of the reduced gradient will be null at the optimum. We proposea presolving procedure that allows us to reduce the dimension of the problem and to begin the resolution algorithm with anappropriate support (basis) that ensures its convergence. For this, the technique of bounding the optimal reduced gradientwill be used. Two numerical illustrative examples are presented, and comparative numerical results are stated on some testproblems to prove the efficiency of our proposed approach.Downloads
Published
2026-10-14
How to Cite
Djemai, S., Bibi, M. O., & Laouar, A. (2026). Presolving a Convex Quadratic Minimization Problem. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-4658
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Copyright (c) 2026 Samia Djemai, Mohand Ouamer Bibi, Abdelhek Laouar
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