Malaysian Journal of Mathematical Sciences, December 2019, Vol. 13(S)
Special Issue: Conference on Mathematics, Informatics and Statistics (CMIS2018)
Comparison between BZAU, SRMI and MRM Conjugate Gradient Methods in Minimization Problems
Lai, L. Y., Ibrahim, N. F., and Mohamed, N. A.
Corresponding Email: [email protected]
Received date: -
Accepted date: -
Abstract:
The conjugate gradient method is one of the best methods that can be used to solve nonlinear unconstrained optimization problems. This
method has gained the interest of researchers and has expanded rapidly. There are many versions of the conjugate gradient method. Each version claims to be efficient. In this paper, we make the comparison among three versions of the conjugate gradient method (MRM, SRMI and BZAU) by using exact line search. The methods were tested in terms of number of iteration and CPU time using 20 standard test functions. The result showed that MRM is the most e cient followed by BZAU and then SRMI. However, BZAU successfully found all the minimizers of the test functions whereas both SRMI and MRM failed at least once. In order to test the robustness of the methods, extensive tests are required.
Keywords: Conjugate gradient method, unconstrained, optimization, line search
