Title of article
A new hybrid conjugate gradient algorithm for unconstrained optimization
Author/Authors
Han ، X. - Southwest University , Zhang ، J. - Southwest University , Chen ، J. - Southwest University
Pages
18
From page
2067
To page
2084
Abstract
In this paper, a new hybrid conjugate gradient algorithm is proposed for solving unconstrained optimization problems. This new method can generate sufficient descent directions unrelated to any line search. Moreover, the global convergence of the proposed method is proved under the Wolfe line search. Numerical experiments are also presented to show the efficiency of the proposed algorithm, especially for solving highly dimensional problems.
Keywords
Unconstrained optimization problem , hybrid conjugate gradient algorithm , sufficient descent directions , global convergence
Journal title
Bulletin of the Iranian Mathematical Society
Serial Year
2017
Journal title
Bulletin of the Iranian Mathematical Society
Record number
2456195
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