Author ORCID Identifier

In this paper, a novel attempt is made to incorporate the two effective algorithm strategies, where BBO has a strong exploration and Salp Swarm Algorithm (SSA) is used for exploitation of the search space. The proposed algorithm is tested on IEEE CEC 2014 and statistical, convergence graphs are given. The proposed algorithm is also applied to 10 real life problems and compared with its counterpart algorithm. Results obtained by above experiments have demonstrated the outperformance of the hybrid version of BBO over other algorithms.

Document Type

Article

Disciplines

Computer Sciences

Publication Details

https://www.sciencedirect.com/science/article/pii/S1110016823003435

Vanita Garg, Kusum Deep, Khalid Abdulaziz Alnowibet, Hossam M. Zawbaa, Ali Wagdy Mohamed, Biogeography Based optimization with Salp Swarm optimizer inspired operator for solving non-linear continuous optimization problems, Alexandria Engineering Journal, Volume 73, 2023, Pages 321-341,

https://doi.org/10.1016/j.aej.2023.04.054

Abstract

In this paper, a novel attempt is made to incorporate the two effective algorithm strategies, where BBO has a strong exploration and Salp Swarm Algorithm (SSA) is used for exploitation of the search space. The proposed algorithm is tested on IEEE CEC 2014 and statistical, convergence graphs are given. The proposed algorithm is also applied to 10 real life problems and compared with its counterpart algorithm. Results obtained by above experiments have demonstrated the outperformance of the hybrid version of BBO over other algorithms.

DOI

https://doi.org/10.1016/j.aej.2023.04.054

Funder

Researchers Supporting Program at King Saud University, (RSP2023R305).

Creative Commons License

Creative Commons Attribution-Share Alike 4.0 International License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.

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