A Survey of Hidden Convex Optimization

Yong Xia

doi:10.1007/s40305-019-00286-5

A Survey of Hidden Convex Optimization

Yong Xia^*

^*Corresponding author for this work

School of Mathematical Sciences

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

Abstract

Motivated by the fact that not all nonconvex optimization problems are difficult to solve, we survey in this paper three widely used ways to reveal the hidden convex structure for different classes of nonconvex optimization problems. Finally, ten open problems are raised.

Original language	English
Pages (from-to)	1-28
Number of pages	28
Journal	Journal of the Operations Research Society of China
Volume	8
Issue number	1
DOIs	https://doi.org/10.1007/s40305-019-00286-5
State	Published - 1 Mar 2020

Keywords

Convex programming
Fractional programming
Lagrangian dual
Quadratic matrix programming
Quadratic programming
Semidefinite programming

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10.1007/s40305-019-00286-5

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title = "A Survey of Hidden Convex Optimization",

abstract = "Motivated by the fact that not all nonconvex optimization problems are difficult to solve, we survey in this paper three widely used ways to reveal the hidden convex structure for different classes of nonconvex optimization problems. Finally, ten open problems are raised.",

keywords = "Convex programming, Fractional programming, Lagrangian dual, Quadratic matrix programming, Quadratic programming, Semidefinite programming",

author = "Yong Xia",

note = "Publisher Copyright: {\textcopyright} 2020, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature.",

year = "2020",

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AB - Motivated by the fact that not all nonconvex optimization problems are difficult to solve, we survey in this paper three widely used ways to reveal the hidden convex structure for different classes of nonconvex optimization problems. Finally, ten open problems are raised.

KW - Convex programming

KW - Fractional programming

KW - Lagrangian dual

KW - Quadratic matrix programming

KW - Quadratic programming

KW - Semidefinite programming

UR - https://www.scopus.com/pages/publications/85077446628

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DO - 10.1007/s40305-019-00286-5

M3 - 文章

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JO - Journal of the Operations Research Society of China

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A Survey of Hidden Convex Optimization

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Keywords

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