Several guaranteed descent conjugate gradient methods for unconstrained optimization (Q1714779)
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scientific article; zbMATH DE number 7010765
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Several guaranteed descent conjugate gradient methods for unconstrained optimization |
scientific article; zbMATH DE number 7010765 |
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Several guaranteed descent conjugate gradient methods for unconstrained optimization (English)
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1 February 2019
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Summary: This paper investigates a general form of guaranteed descent conjugate gradient methods which satisfies the descent condition \(g^T_k d_k\leq -(1-1/(4\theta_k))\| g_k\|^2\) (\(\theta_k>1/4\)) and which is strongly convergent whenever the weak Wolfe line search is fulfilled. Moreover, we present several specific guaranteed descent conjugate gradient methods and give their numerical results for large-scale unconstrained optimization.
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0.8811041712760925
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