The PPADMM Method for Solving Quadratic Programming Problems

Hai-Long Shen and Xu Tang
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Hai-Long Shen: Department of Mathematics College of Sciences, Northeastern University Shenyang, Shenyang 100819, China
Xu Tang: Northwest Institute of Mechanical and Electrical Engineering Xianyang, Xianyang 712000, China

Mathematics, 2021, vol. 9, issue 9, 1-15

Abstract: In this paper, a preconditioned and proximal alternating direction method of multipliers (PPADMM) is established for iteratively solving the equality-constraint quadratic programming problems. Based on strictly matrix analysis, we prove that this method is asymptotically convergent. We also show the connection between this method with some existing methods, so it combines the advantages of the methods. Finally, the numerical examples show that the algorithm proposed is efficient, stable, and flexible for solving the quadratic programming problems with equality constraint.

Keywords: quadratic programming problem; global convergence; preconditioning and proximal terms; iterative methods; convex problems (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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