A New Conjugate Gradient Method for Unconstrained Optimization
Zuhua Zhang
Abstract
Zuhua Zhang
Abstract
In this paper we present a new nonlinear cojugate gradient method for unconstraind optimization problems and prove its local convergence.Numerical results show that the new conjugate gradient method is effective and superior to other similar methods.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In this paper we present a new nonlinear cojugate gradient method for unconstraind optimization problems and prove its local convergence.Numerical results show that the new conjugate gradient method is effective and superior to other similar methods.
Key concepts: Nonlinear conjugate gradient method, Conjugate gradient method, Mathematics, Derivation of the conjugate gradient method, Gradient method, Conjugate residual method, Convergence (economics), Biconjugate gradient method