Implementation of combined new optimal cuckoo algorithm with a gray wolf algorithm to solve unconstrained optimization nonlinear problems
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...
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| Main Authors: | , |
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| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2020-09-01.
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| Subjects: | |
| Online Access: | Get fulltext Get fulltext |
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| Summary: | 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. |
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| Item Description: | https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21583 |