| Autor: |
Madhukar, Ellendula, Ragunathan, Thirumalaisamy |
| Předmět: |
|
| Zdroj: |
Revue d'Intelligence Artificielle; Apr2022, Vol. 36 Issue 2, p327-332, 6p |
| Abstrakt: |
In the era of enhancing demand for online resources cloud is emerging as the greatest cutting edge technologies to serve the requirements. With volatility in the usage of the cloud resources, it is a tough task to serve the user requirements. Heuristic algorithms, Meta heuristic algorithms are trending these days, as they are helping to find the nearby optimal solutions within a reasonable time. But they suffer from either slow convergence or with premature solutions. It is evident that NP-complete algorithms take exponential time to find an efficient and optimal solution. This paper hybridizes grey wolf optimization along with Crow search algorithm. This balances the exploration and exploitation. The experimental results prove that the proposed algorithm is on par with existing algorithms and at times it shows better performance. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
