A sufficient descent conjugate gradient method and its global convergence |
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| Authors: | Yunlong Cheng Qiong Mou Xianbing Pan Shengwei Yao |
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| Affiliation: | 1. College of Mobile Telecommunications, Chongqing University of Posts and Telecommunications, Chongqing 40065, People's Republic of China;2. School of Mathematics and Physics, Chongqing University of Posts and Telecommunications, Chongqing 40065, People's Republic of China;3. School of Information and Statistics, Guangxi University of Finance and Economics, Nanning 530003, People's Republic of China |
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| Abstract: | In this paper, a DL-type conjugate gradient method is presented. The given method is a modification of the Dai–Liao conjugate gradient method. It can also be considered as a modified LS conjugate gradient method. For general objective functions, the proposed method possesses the sufficient descent condition under the Wolfe line search and is globally convergent. Numerical comparisons show that the proposed algorithm slightly outperforms the PRP+ and CG-descent gradient algorithms as well as the Barzilai–Borwein gradient algorithm. |
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| Keywords: | conjugate gradient method unconstrained optimization global convergence Wolfe linesearch |
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