Journal
OPERATIONS RESEARCH LETTERS
Volume 49, Issue 4, Pages 543-547Publisher
ELSEVIER
DOI: 10.1016/j.orl.2021.06.001
Keywords
Fractional programming; Minimax optimization; Quadratic programming; Semidefinite programming; Global optimization
Categories
Funding
- National Natural Science Foundation of China [11822103, 11571029]
- Beijing Natural Science Foundation [Z180005]
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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.
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