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Rana Zaidan Alkawaz
Department of Mathematics/ College of Basic Education / University of Telafer/ Iraq.

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1582-1589

Abstract

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.
Co-Authors Ali Abbas Al-Arabo