A new class of conjugate gradient methods for unconstrained smooth optimization and absolute value equations

被引:0
|
作者
Farzad Rahpeymaii
Keyvan Amini
Tofigh Allahviranloo
Mohsen Rostamy Malkhalifeh
机构
[1] Islamic Azad University,Department of Mathematics, Science and Research Branch
[2] Razi University,Department of Mathematics, Faculty of Sciences
来源
Calcolo | 2019年 / 56卷
关键词
Conjugate gradient method; Smooth optimization; Conjugate subgradient method; Absolute value equations; Wolfe conditions; 90C30; 93E24; 34A34;
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摘要
In this paper, we introduce a new three-term conjugate gradient (NTTCG) method to solve unconstrained smooth optimization problems. NTTCG is based on conjugate gradient methods proposed by Dai and Yuan (SIAM J Optim 10:177–182, 1999) and Polak and Ribière (Rev Francaise Inform Rech Oper 3(16):35–43, 1969). The descent property of the direction generated by NTTCG in each iteration is established. Under some standard assumptions, the global convergence results of the new methods are investigated. The extension of this algorithm is proposed to solve absolute value equations (AVE), called three-term conjugate subgradient (NTTCS) method. Numerical experiments are reported for unconstrained CUTEst problems and AVE.
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