A New Hybrid HS-DY Conjugate Gradient Method
- Resource Type
- Conference
- Authors
- Dong, Junli; Jiao, Baocong; Chen, Lanping
- Source
- 2011 Fourth International Joint Conference on Computational Sciences and Optimization Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on. :94-98 Apr, 2011
- Subject
- Robotics and Control Systems
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Gradient methods
Convergence
High definition video
Software
Programming
Unconstrained optimization
Conjugate gradient method
Wolfe line search
Global convergence
- Language
Conjugate gradient method is one of the most useful methods for solving unconstrained optimization problem. In this paper, we propose a hybrid conjugate gradient method for unconstrained optimization based on the Hestenes-Stiefel and Dai-Yuan conjugate gradient Algorithms. By searching a particular direction, the new algorithm satisfies the descent condition. Furthermore under the Wolfe line search conditions, we prove that the new method can support the global convergence. The initial numerical experiments show that the new algorithm is efficient.