Tunicate Swarm Algorithm (TSA)

version 7.0.0 (3.46 MB) by xsjsh
A Novel Bio-inspired Optimization Algorithm

151 Downloads

Updated 13 Nov 2021

View License

TSA algorithm imitates jet propulsion and swarm behaviors of tunicates during the navigation
and foraging process. The performance of TSA is evaluated on seventy-four benchmark test problems employing sensitivity, convergence and scalability analysis along with ANOVA test. The efficacy of this algorithm is further compared with several well-regarded metaheuristic approaches based on the generated optimal solutions. In addition, we also executed the proposed algorithm on six constrained and one unconstrained engineering design problems to further verify its robustness. The simulation results demonstrate that TSA generates better
optimal solutions in comparison to other competitive algorithms and is capable of solving real case studies having unknown search spaces.
Cite this paper as: Kaur, S., Awasthi, L. K., Sangal, A. L., & Dhiman, G. (2020). Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization. Engineering Applications of Artificial Intelligence, 90, 103541.

Cite As

xsjsh (2022). Tunicate Swarm Algorithm (TSA) (https://www.mathworks.com/matlabcentral/fileexchange/101954-tunicate-swarm-algorithm-tsa), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2021b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!