Biogeography Based optimization with Salp Swarm optimizer inspired operator for solving non-linear continuous optimization problems
Copyright policy )Biogeography Based optimization with Salp Swarm optimizer inspired operator for solving non-linear continuous optimization problems
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.
- Cairo University Egypt
- School of Computer Science Switzerland
- King Saud University Saudi Arabia
- Technological University Dublin Ireland
- Indian Institutes of Technology India
Stochastic algorithms, Salp Swarm Algorithm, Exploration, Electrical and Computer Engineering, Exploitation, TA1-2040, Engineering (General). Civil engineering (General), Biogeography Based Optimization, 004
Stochastic algorithms, Salp Swarm Algorithm, Exploration, Electrical and Computer Engineering, Exploitation, TA1-2040, Engineering (General). Civil engineering (General), Biogeography Based Optimization, 004
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