CGOPT swMATH ID: 10952 Software Authors: Kou, Caixia Description: An improved nonlinear conjugate gradient method with an optimal property. Conjugate gradient methods have played a special role in solving large scale nonlinear problems. Recently, the author and Dai proposed an efficient nonlinear conjugate gradient method called CGOPT, through seeking the conjugate gradient direction closest to the direction of the scaled memoryless BFGS method. In this paper, we make use of two types of modified secant equations to improve CGOPT method. Under some assumptions, the improved methods are showed to be globally convergent. Numerical results are also reported Homepage: http://link.springer.com/article/10.1007%2Fs11425-013-4682-1 Keywords: nonlinear conjugate gradient; CGOPT; unconstrained optimization; global convergence; modified secant equation Related Software: SCALCG; ve08; ACGSSV; CUTEr; SifDec Cited in: 9 Publications all top 5 Cited by 22 Authors 2 Dong, Xiaoliang 2 Wang, Zhan 2 Yao, Shengwei 2 Yuan, Gonglin 1 Abashar, Abdelrhaman 1 Cao, Mingyuan 1 Chen, Yuting 1 Dai, Zhifeng 1 Feng, Qinliang 1 Ghanbari, Reza 1 He, Yubo 1 Kou, Caixia 1 Li, Lue 1 Li, Pengyuan 1 Li, Xiangli 1 Liu, Hongwei 1 Lu, Junyu 1 Mamat, Mustafa Bin 1 Ning, Liangshuo 1 Rivaie, Mohd 1 Xu, Jieqiong 1 Yang, Yueting all top 5 Cited in 8 Serials 2 Applied Numerical Mathematics 1 Applied Mathematics and Computation 1 Calcolo 1 Journal of Computational and Applied Mathematics 1 Journal of Optimization Theory and Applications 1 Journal of Inequalities and Applications 1 Science China. Mathematics 1 Journal of the Operations Research Society of China Cited in 3 Fields 9 Operations research, mathematical programming (90-XX) 5 Numerical analysis (65-XX) 3 Calculus of variations and optimal control; optimization (49-XX) Citations by Year