A Variant Hybrid Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization

DOI

10.2991/iceep-18.2018.24How to use a DOI?

Keywords

Conjugate gradient; Unconstrained optimization; Global convergence

Abstract

In this paper, we have presented a new hybrid conjugate gradient algorithm for solving unconstrained optimization problems. The parameter is a convex combination of the PRP and FR conjugate gradient methods. Under general wolfe line search conditions, we proved the global convergence of the algorithm. The numerical results show that the proposed methods are effective.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhijun Luo
AU  - Lirong Wang
AU  - Guohua Chen
PY  - 2018/09
DA  - 2018/09
TI  - A Variant Hybrid Conjugate Gradient Algorithm for Large-Scale Unconstrained Optimization
BT  - Proceedings of the 2018 7th International Conference on Energy and Environmental Protection (ICEEP 2018)
PB  - Atlantis Press
SP  - 146
EP  - 149
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceep-18.2018.24
DO  - 10.2991/iceep-18.2018.24
ID  - Luo2018/09
ER  -