An efficient PGM-based algorithm with backtracking strategy for solving quadratic optimization problems with spherical constraint

被引:0
|
作者
Tang, Yaozong [1 ]
Luo, Gang [2 ,3 ]
Yang, Qingzhi [2 ,3 ]
机构
[1] Kashi Univ, Res Ctr Modern Math & its Applicat, Sch Math & Stat, Kashi 844000, Peoples R China
[2] Nankai Univ, Sch Math Sci, Tianjin 300071, Peoples R China
[3] Nankai Univ, LPMC, Tianjin 300071, Peoples R China
基金
美国国家科学基金会;
关键词
Global convergence; Quadratic programming; Projected gradient method; Trust region subproblem; TRUST-REGION SUBPROBLEM;
D O I
10.1016/j.cam.2022.114915
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We utilize projected gradient method (PGM for short) to solve quadratic optimization problem with spherical constraint. Based on the global convergence of simple first order conic method for trust region subproblem, we show that under some conditions, the global convergence of the PGM is guaranteed if the initial point is chosen specially. With only the multiplication of matrix and vector involved, a good approximation solution can be obtained in a low computation cost for large scale applications.(c) 2022 Elsevier B.V. All rights reserved.
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页数:13
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