Fast algorithm for singly linearly constrained quadratic programs with box-like constraints

Meijiao Liu () and Yong-Jin Liu ()
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Meijiao Liu: Shenyang Aerospace University
Yong-Jin Liu: Shenyang Aerospace University

Computational Optimization and Applications, 2017, vol. 66, issue 2, No 5, 309-326

Abstract: Abstract This paper focuses on a singly linearly constrained class of convex quadratic programs with box-like constraints. We propose a new fast algorithm based on parametric approach and secant approximation method to solve this class of quadratic problems. We design efficient implementations for our proposed algorithm and compare its performance with two state-of-the-art standard solvers called Gurobi and Mosek. Numerical results on a variety of test problems demonstrate that our algorithm is able to efficiently solve the large-scale problems with the dimension up to fifty million and it substantially outperforms Gurobi and Mosek in terms of the running time.

Keywords: Singly linearly constrained quadratic programs; Secant method; Weighted Ky Fan k-norm; 90C20; 90C25 (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10589-016-9863-8

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