| Summary: | One of the commonly used optimization methods is the conjugate gradient (CG) method. This method is highly practical for solving large scale problems and applicable for real life. This study suggests another CG method that fulfills the sufficient descent and global convergence properties. The robustness and efficiency of the proposed method are evaluated by comparison with other established CG methods. The numerical testing uses sixteen test functions in MATLAB subroutine programming under strong Wolfe line search. Numerically, the result concludes that the new CG method has the best performance in term of iteration number (NOI) and CPU time. This method is then implemented for solving linear regression model in order to show its applicability. Hence, this method has been proven to be successful. © BEIESP.
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