Solving a large scale nonlinear unconstrained optimization with exact line search direction by using new coefficient of conjugate gradient methods

Mustafa, Mamat and Mohamed, N.S. and Rivaie, M (2016) Solving a large scale nonlinear unconstrained optimization with exact line search direction by using new coefficient of conjugate gradient methods. In: 4th International Conference on Fundamental and Applied Sciences, 15-17 Aug 2016, Kuala Lumpur.

Image FH03-FIK-16-07678.jpg Restricted to Registered users only Download (166kB)

Abstract

Conjugate gradient (CG) methods are one of the tools in optimization. Due to its low computational memory requirement, this method is used in solving several of nonlinear unconstrained optimization problems from designs, economics, physics and engineering. In this paper, a new modification of CG family coefficient (βk) is proposed and posses global convergence under exact line search direction. Numerical experimental results based on the number of iterations and central processing unit (CPU) time show that the new βk performs better than some other well known CG methods under some standard test functions.

Actions (login required)

View Item