TY - JOUR
T1 - A Survey of Hidden Convex Optimization
AU - Xia, Yong
N1 - Publisher Copyright:
© 2020, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - 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.
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
U2 - 10.1007/s40305-019-00286-5
DO - 10.1007/s40305-019-00286-5
M3 - 文章
AN - SCOPUS:85077446628
SN - 2194-668X
VL - 8
SP - 1
EP - 28
JO - Journal of the Operations Research Society of China
JF - Journal of the Operations Research Society of China
IS - 1
ER -