A new direction search of hybrid quasi-Newton

Evar Lutfalla Sadraddin (Salahaddin University-Erbil)
Ivan Subhi Latif (Salahaddin University-Erbil)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 27, No 1: July 2022

A new hybrid quasi-Newton search direction ( HQNEI ) is proposed. It uses the update formula of Broyden–Fletcher–Goldfarb–Shanno (BFGS) with a certain conjugate gradient (CG) parameter by a nested direction. The global convergence analysis and superlinear rate, addtionaly with sufficient descent are proved using exact line search. Finally, the computation comparisons are made with original hybrid parents; BFGS and CG, through the efficiency in terms of iteration numbers and CPU-running time showing the superior of HQNEI. Therefore, the results marked preference of HQNEI from other two producer algorithms.