Rat Swarm Optimizer (RSO)
This work presents a novel bio-inspired optimization algorithm called Rat Swarm Optimizer (RSO) for solving the challenging optimization problems. The main inspiration of this optimizer is the chasing and attacking behaviors of rats in nature. This paper mathematically models these behaviors and benchmarks on a set of 38 test problems to ensure its applicability on different regions of search space. The RSO algorithm is compared with eight well-known optimization algorithms to validate its performance. It is then employed on six real-life constrained engineering design problems. The convergence and computational analysis are also investigated to test exploration, exploitation, and local optima avoidance of proposed algorithm. The experimental results reveal that the proposed RSO algorithm is highly effective in solving real world optimization problems as compared to other well-known optimization algorithms.
This is the source code of the paper: Gaurav Dhiman et al. "A novel algorithm for global optimization: Rat Swarm Optimizer" Journal of Ambient Intelligence and Humanized Computing, Springer https://link.springer.com/article/10.1007/s12652-020-02580-0
More information can be found in: http://dhimangaurav.com/
Cite As
Gaurav Dhiman (2024). Rat Swarm Optimizer (RSO) (https://www.mathworks.com/matlabcentral/fileexchange/87057-rat-swarm-optimizer-rso), MATLAB Central File Exchange. Retrieved .
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RSO
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1.0.0 |