Tunicate Swarm Algorithm (TSA)

版本 3.0.0 (3.4 MB) 作者: Gaurav Dhiman
A Novel Bio-inspired Optimization Algorithm
834.0 次下载
更新时间 2022/7/4

查看许可证

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.

引用格式

Gaurav Dhiman (2024). Tunicate Swarm Algorithm (TSA) (https://www.mathworks.com/matlabcentral/fileexchange/75182-tunicate-swarm-algorithm-tsa), MATLAB Central File Exchange. 检索来源 .

MATLAB 版本兼容性
创建方式 R2020a
兼容任何版本
平台兼容性
Windows macOS Linux

Community Treasure Hunt

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

Start Hunting!
版本 已发布 发行说明
3.0.0

Version 3.0.0

2.0.0

Updated version.

1.0.0