Conjugate gradient methods based on secant conditions that generate descent search directions for unconstrained optimization

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Conjugate gradient methods based on secant conditions that generate descent search directions for unconstrained optimization

Conjugate gradient methods have been paid attention to, because they can be directly applied to large-scale unconstrained optimization problems. In order to incorporate second order information of the objective function into conjugate gradient methods, Dai and Liao (2001) proposed a conjugate gradient method based on the secant condition. However, their method does not necessarily generate a de...

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ژورنال

عنوان ژورنال: Journal of Computational and Applied Mathematics

سال: 2012

ISSN: 0377-0427

DOI: 10.1016/j.cam.2012.01.036