Open AccessImplementation of combined new optimal cuckoo algorithm with a gray wolf algorithm to solve unconstrained optimization nonlinear problems
Author(s) -
Ali Abbas Al-Arabo,
Rana Z. Al-Kawaz
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v19.i3.pp1582-1589
Subject(s) - cuckoo , algorithm , convergence (economics) , nonlinear system , cuckoo search , optimization algorithm , mathematical optimization , computer science , mathematics , particle swarm optimization , zoology , physics , quantum mechanics , economics , biology , economic growth
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.