Journal of the Operations Research Society of China ›› 2020, Vol. 8 ›› Issue (1): 1-28.doi: 10.1007/s40305-019-00286-5

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  • 收稿日期:2019-01-31 修回日期:2019-05-24 出版日期:2020-03-30 发布日期:2020-02-18
  • 通讯作者: Yong Xia E-mail:yxia@buaa.edu.cn
  • 基金资助:
    This research was supported by the National Natural Science Foundation of China (Nos. 11822103, 11571029) and Natural Science Foundation of Beijing (No. Z180005).

A Survey of Hidden Convex Optimization

Yong Xia   

  1. Key Laboratory of Mathematics, Informatics and Behavioral Semantics of the Ministry of Education, School of Mathematics and System Sciences, Beihang University, Beijing 100191, China
  • Received:2019-01-31 Revised:2019-05-24 Online:2020-03-30 Published:2020-02-18
  • Contact: Yong Xia E-mail:yxia@buaa.edu.cn

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.

Key words: Convex programming, Quadratic programming, Quadratic matrix programming, Fractional programming, Lagrangian dual, Semidefinite programming

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