A strongly convergent norm-relaxed method of strongly sub-feasible direction for optimization with nonlinear equality and inequality constraints. - Jin-Bao Jian; Qing-Juan Xu; Dao-Lan Han (Appl. Math. Comput., 2006)

A norm-relaxed method of feasible directions for finely discretized problems from semi-infinite programming. - Jin-Bao Jian; Qing-Juan Xu; Dao-Lan Han (Eur. J. Oper. Res., 2008)

A fast convergent sequential linear equation method for inequality constrained optimization without strict complementarity. - Jinbao Jian; Dao-Lan Han; Qing-Juan Xu (Appl. Math. Comput., 2014)

A family of inertial derivative-free projection methods for constrained nonlinear pseudo-monotone equations with applications. - Jinbao Jian; Jianghua Yin; Chunming Tang 002; Dao-Lan Han (Comput. Appl. Math., 2022)

Two modified conjugate gradient methods for unconstrained optimization with applications in image restoration problems. - Guodong Ma; Hui Lin; Wenhui Jin; Dao-Lan Han (J. Appl. Math. Comput., 2022)

A modified inertial three-term conjugate gradient projection method for constrained nonlinear equations with applications in compressed sensing. - Guodong Ma; Jiachen Jin; Jinbao Jian; Jianghua Yin; Dao-Lan Han (Numer. Algorithms, 2023)

An effective inertial-relaxed CGPM for nonlinear monotone equations. - Jinbao Jian; Zhiwen Ren; Jianghua Yin; Dao-Lan Han; Xiaodi Wu 002 (J. Appl. Math. Comput., 2024)

A family of accelerated hybrid conjugate gradient method for unconstrained optimization and image restoration. - Xiaodi Wu 002; Xiaomin Ye; Dao-Lan Han (J. Appl. Math. Comput., 2024)

An indefinite proximal Peaceman-Rachford splitting method-based algorithm integrating the generalization acceleration technique for separable convex programming problems in image restoration. - Xianke Tang; Jianghua Yin; Dan Jian; Dao-Lan Han (J. Comput. Appl. Math., 2025)