Quadratic double-ratio minimax optimization

被引：4
作者：
Zare, Arezu [1 ]
Ashrafi, Ali [1 ]
Xia, Yong [2 ]
机构：
[1] Semnan Univ, Fac Math Stat & Comp Sci, Semnan, Iran
[2] Beihang Univ, LMIB, Minist Educ, Sch Math & Syst Sci, Beijing 100191, Peoples R China
来源：
OPERATIONS RESEARCH LETTERS | 2021年 / 49卷 / 04期
基金：
北京市自然科学基金; 中国国家自然科学基金;
关键词：
Fractional programming; Minimax optimization; Quadratic programming; Semidefinite programming; Global optimization; REGULARIZATION; ALGORITHM;
D O I：
10.1016/j.orl.2021.06.001
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
The quadratic double-ratio minimax optimization (QRM) admits a generalized linear conic fractional reformulation. It leads to two algorithms to globally solve (QRM) from the primal and dual sides, respectively. The hidden convexity of (QRM) remains unknown except for the special case when both denominators are equal. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码：543 / 547
页数：5
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