Hybrid Conjugate Gradient Algorithm for Unconstrained Optimization

Volume: 141, Issue: 2, Pages: 249 - 264
Published: Dec 31, 2008
Abstract
In this paper a new hybrid conjugate gradient algorithm is proposed and analyzed. The parameter β k is computed as a convex combination of the Polak-Ribière-Polyak and the Dai-Yuan conjugate gradient algorithms, i.e. β =(1−θ k )β +θ k β . The parameter θ k in the convex combination is computed in such a way that the conjugacy condition is satisfied, independently of the line search. The line search uses the standard Wolfe conditions. The...
Paper Details
Title
Hybrid Conjugate Gradient Algorithm for Unconstrained Optimization
Published Date
Dec 31, 2008
Volume
141
Issue
2
Pages
249 - 264
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