Nonlinear conjugate gradient methods with sufficient descent condition for large-scale unconstrained optimization (Q1036299)
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scientific article; zbMATH DE number 5632454
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Nonlinear conjugate gradient methods with sufficient descent condition for large-scale unconstrained optimization |
scientific article; zbMATH DE number 5632454 |
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Nonlinear conjugate gradient methods with sufficient descent condition for large-scale unconstrained optimization (English)
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13 November 2009
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Summary: Two nonlinear conjugate gradient-type methods for solving unconstrained optimization problems are proposed. An attractive property of the methods, is that, without any line search, the generated directions always descend. Under some mild conditions, global convergence results for both methods are established. Preliminary numerical results show that these proposed methods are promising, and competitive with the well-known PRP method.
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large-scale
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comparison of methods
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nonlinear conjugate gradient-type methods
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unconstrained optimization
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global convergence
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numerical results
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PRP method
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