期刊
OPERATIONS RESEARCH LETTERS
卷 49, 期 4, 页码 543-547出版社
ELSEVIER
DOI: 10.1016/j.orl.2021.06.001
关键词
Fractional programming; Minimax optimization; Quadratic programming; Semidefinite programming; Global optimization
资金
- National Natural Science Foundation of China [11822103, 11571029]
- Beijing Natural Science Foundation [Z180005]
The quadratic double-ratio minimax optimization (QRM) can be reformulated as a generalized linear conic fractional form, leading to two algorithms for global solutions from primal and dual perspectives. The hidden convexity of (QRM) is still unknown except for the special case when both denominators are equal.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据
分享论文
