Implementation of combined new optimal cuckoo algorithm with a gray wolf algorithm to solve unconstrained optimization nonlinear problems

Ali Abbas Al-Arabo (College of Arts, University of Mosul, Mosul, Iraq.)
Rana Zaidan Alkawaz (Department of Mathematics/ College of Basic Education / University of Telafer/ Iraq.)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 19, No 3: September 2020

In this article, a combined optimization algorithm was proposed which combines the optimal adaptive cuckoo algorithm (OACS) which is Nature-inspired algorithm with gray wolf optimizer algorithm (GWO). Sometimes considering the cuckoo algorithm alone, may fail to find the local minimum-point and also fails to reach to the solution because of the slow speed of its convergence property. Therefore, considering the new proposed adaptive combined algorithm gave a strong improvement for using this to reach the minimum point in solving (23) nonlinear test problems. This is suitable to solve a large number of nonlinear unconstraint optimization test functions with obtaining good and robust numerical results.