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Biogeography Based optimization with Salp Swarm optimizer inspired operator for solving non-linear continuous optimization problems
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DOI：10.1016/j.aej.2023.04.054.png)
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Abstract
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In this paper, a novel attempt is made to incorporate the two effective algorithm strate-gies, 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, conver-gence graphs are given. The proposed algorithm is also applied to 10 real life problems and com-pared with its counterpart algorithm. Results obtained by above experiments have demonstrated the outperformance of the hybrid version of BBO over other algorithms. (c) 2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
Keywords:
Salp Swarm Algorithm
Biogeography Based Opti-mization
Exploitation
Exploration
Stochastic algorithms
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