Release time:2016-04-23
Affiliation of Author(s):Central South University
Journal:JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
Abstract:In this paper, an improved spectral conjugate gradient algorithm is developed for solving nonconvex unconstrained optimization problems. Different from the existent methods, the spectral and conjugate parameters are chosen such that the obtained search direction is always sufficiently descent as well as being close to the quasi-Newton direction. With these suitable choices, the additional assumption in the method proposed by Andrei on the boundedness of the spectral parameter is removed. Under some mild conditions, global convergence is established. Numerical experiments are employed to demons
Co-author:Xiaohong Chen
First Author:Songhai Deng
Indexed by:Unit Twenty Basic Research
Correspondence Author:Zhong Wan
Document Type:J
Volume:157
Issue:3
Page Number:820-842
Translation or Not:no
Date of Publication:2013-06-01
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