On Characterizations of D-η-Properly Prequasi-Invex Function. - Huixian Wu; Hezhi Luo (J. Syst. Sci. Complex., 2007)

On the Convergence of Augmented Lagrangian Methods for Constrained Global Optimization. - Hezhi Luo; Xiaoling Sun 001; Duan Li 002 (SIAM J. Optim., 2007)

Convergence properties of augmented Lagrangian methods for constrained global optimization. - Hezhi Luo; Xiaoling Sun 001; Huixian Wu (Optim. Methods Softw., 2008)

The global convergence of augmented Lagrangian methods based on NCP function in constrained nonconvex optimization. - Huixian Wu; Hezhi Luo; S. L. Li (Appl. Math. Comput., 2009)

On the convergence properties of modified augmented Lagrangian methods for mathematical programming with complementarity constraints. - Hezhi Luo; Xiaoling Sun 001; Yifan Xu 001; Huixian Wu (J. Glob. Optim., 2010)

On the convergence of augmented Lagrangian methods for nonlinear semidefinite programming. - Hezhi Luo; Huixian Wu; Guangting Chen (J. Glob. Optim., 2012)

Saddle points of general augmented Lagrangians for constrained nonconvex optimization. - Huixian Wu; Hezhi Luo (J. Glob. Optim., 2012)

Global convergence of modified augmented Lagrangian methods for nonlinear semidefinite programming. - Huixian Wu; Hezhi Luo; Xiaodong Ding; Guanting Chen 003 (Comput. Optim. Appl., 2013)

Some Results on Augmented Lagrangians in Constrained Global Optimization via Image Space Analysis. - Hezhi Luo; Huixian Wu; Jianzhen Liu (J. Optim. Theory Appl., 2013)

Nonlinear separation approach for the augmented Lagrangian in nonlinear semidefinite programming. - Huixian Wu; Hezhi Luo; Jianfang Yang (J. Glob. Optim., 2014)

Semi-definite programming relaxation of quadratic assignment problems based on nonredundant matrix splitting. - Jiming Peng; Tao Zhu; Hezhi Luo; Kim-Chuan Toh (Comput. Optim. Appl., 2015)

On Saddle Points in Semidefinite Optimization via Separation Scheme. - Hezhi Luo; Huixian Wu; Jianzhen Liu (J. Optim. Theory Appl., 2015)

Enhancing Semidefinite Relaxation for Quadratically Constrained Quadratic Programming via Penalty Methods. - Hezhi Luo; Xiaodi Bai; Jiming Peng (J. Optim. Theory Appl., 2019)

New global algorithms for quadratic programming with a few negative eigenvalues based on alternative direction method and convex relaxation. - Hezhi Luo; Xiaodi Bai; Gino J. Lim; Jiming Peng (Math. Program. Comput., 2019)

An efficient global algorithm for worst-case linear optimization under uncertainties based on nonlinear semidefinite relaxation. - Xiaodong Ding; Hezhi Luo; Huixian Wu; Jianzhen Liu (Comput. Optim. Appl., 2021)

Complexity Results and Effective Algorithms for Worst-Case Linear Optimization Under Uncertainties. - Hezhi Luo; Xiaodong Ding; Jiming Peng; Rujun Jiang; Duan Li 002 (INFORMS J. Comput., 2021)

Convergence analysis of modified pth power Lagrangian algorithms with alternative updating strategies for constrained nonconvex optimization. - Huixian Wu; Hezhi Luo; Fangying Zheng; Jianfang Yang (J. Comput. Appl. Math., 2021)

A new branch-and-cut algorithm for non-convex quadratic programming via alternative direction method and semidefinite relaxation. - Hezhi Luo; Sikai Chen; Huixian Wu (Numer. Algorithms, 2021)

Effective algorithms for separable nonconvex quadratic programming with one quadratic and box constraints. - Hezhi Luo; Xianye Zhang; Huixian Wu; Weiqiang Xu (Comput. Optim. Appl., 2023)

An effective global algorithm for worst-case linear optimization under polyhedral uncertainty. - Huixian Wu; Hezhi Luo; Xianye Zhang; Haiqiang Qi (J. Glob. Optim., 2023)

A new global algorithm for factor-risk-constrained mean-variance portfolio selection. - Huixian Wu; Hezhi Luo; Xianye Zhang; Jianzhen Liu (J. Glob. Optim., 2023)

Fast Globally Optimal Computational Offloading and Service Caching in Container-Based Edge Computing Systems. - Qi Zhang 093; Weiqiang Xu; Hezhi Luo; Shuyun Luo (IEEE Internet Things J., 2024)

A New branch-and-cut algorithm for linear sum-of-ratios problem based on SLO method and LO relaxation. - Hezhi Luo; Youmin Xu; Huixian Wu; Guoqiang Wang (Comput. Optim. Appl., 2025)