Seagull Optimization Algorithm (SOA)
The main inspiration of this algorithm is the migration and attacking behaviors of a seagull in nature. These behaviors are mathematically modeled and implemented to emphasize exploration and exploitation in a given search space. The performance of SOA algorithm
is compared with nine well-known metaheuristics on forty-four benchmark test functions. The analysis of computational complexity and convergence behaviors of the proposed algorithm have been evaluated. It is then employed to solve seven constrained real-life industrial applications to demonstrate its applicability. Experimental results reveal that the proposed algorithm is able to solve challenging large-scale constrained problems and is very competitive algorithm as compared with other optimization algorithms.
Cite it as: Dhiman, G., & Kumar, V. (2019). Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems. Knowledge-Based Systems, 165, 169-196.
Cita come
Gaurav Dhiman (2024). Seagull Optimization Algorithm (SOA) (https://www.mathworks.com/matlabcentral/fileexchange/75180-seagull-optimization-algorithm-soa), MATLAB Central File Exchange. Recuperato .
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