A Full-Newton Step Interior-Point Method for Weighted Quadratic Programming Based on the Algebraic Equivalent Transformation

Yongsheng Rao, Jianwei Su and Behrouz Kheirfam ()
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Yongsheng Rao: Institute of Computing Science and Technology, Guangzhou University, Guangzhou 510006, China
Jianwei Su: Institute of Computing Science and Technology, Guangzhou University, Guangzhou 510006, China
Behrouz Kheirfam: Department of Mathematics, Azarbaijan Shahid Madani University, Tabriz 5375171379, Iran

Mathematics, 2024, vol. 12, issue 7, 1-11

Abstract: In this paper, a new full-Newton step feasible interior-point method for convex quadratic programming is presented and analyzed. The idea behind this method is to replace the complementarity condition with a non-negative weight vector and use the algebraic equivalent transformation for the obtained equation. Under the selection of appropriate parameters, the quadratic rate of convergence of the new algorithm is established. In addition, the iteration complexity of the algorithm is obtained. Finally, some numerical results are presented to demonstrate the practical performance of the proposed algorithm.

Keywords: quadratic programming; interior-point methods; full-Newton step; weight vector (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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