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

Ali Abbas Al-Arabo, Rana Zaidan Alkawaz


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.


adaptive Cuckoo algorithm; Gray Wolf algorithm; combined algorithm; minimum point; unconstraint optimization

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