Journal of Algorithms and Computation
Open Access

An Accelerated Active-Set Algorithm for Convex Quadratic Programming

Document Type : Research Paper

Authors

Negin Bagherpour 1
Nima Minayi 2
Amirhossein Shanaghi 3

1 Department of Engineering Sciences, University of Tehran

2 Department of Engineering Sciences, University of Tehran, Tehran, Iran

3 Department of Engineering Sciences, University of Tehran, Tehran, Iran.

https://doi.org/10.22059/jac.2026.417507.1263
Abstract
Convex quadratic programming (QP) arises in many applications such as control theory, economics, and robotics. In this paper, we propose two active-set schemes for solving convex QP problems by exploiting structural properties of the Karush–Kuhn–Tucker (KKT) system. The proposed methods are implemented and tested on randomly generated problems as well as benchmark instances from the CUTEst test collection. In total, 2000 numerical experiments are conducted to evaluate the performance of the algorithms. The numerical results indicate that the proposed approaches reduce computational time compared with the classical active-set method, with the first strategy performing better for problems with few constraints and the second showing improved efficiency when the number of independent constraints is large.

Keywords

Quadratic programming
Active Set
SVD
Spectral Decomposition
KKT
Journal of Algorithms and Computation
Volume 58, Issue 1
July 2026
Pages 49-59

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