New Hybrid Conjugate Gradient Algorithms for Unconstrained Optimization

Abstract

New hybrid conjugate gradient algorithms are proposed and analyzed. In these hybrid algorithms the famous parameter k β is computed as a convex combination of the Polak-Ribière-Polyak and Dai-Yuan conjugate gradient algorithms. In one hybrid algorithm the parameter in convex combination is computed in such a way that the conjugacy condition is satisfied… (More)
DOI: 10.1007/978-0-387-74759-0_441

Topics

11 Figures and Tables

Cite this paper

@inproceedings{Andrei2009NewHC, title={New Hybrid Conjugate Gradient Algorithms for Unconstrained Optimization}, author={Neculai Andrei}, booktitle={Encyclopedia of Optimization}, year={2009} }