AUTHOR=Zhang Tian , Zhou Yongquan , Zhou Guo , Deng Wu , Luo Qifang 

TITLE=Bioinspired Bare Bones Mayfly Algorithm for Large-Scale Spherical Minimum Spanning Tree

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.830037

DOI=10.3389/fbioe.2022.830037

ISSN=2296-4185

ABSTRACT=Mayfly algorithm (MA) is a bio-inspired algorithm based on population proposed in recent years and has been successfully applied to many engineering problems. However, it has too many parameters, which makes it difficult to set and adjust a set of appropriate parameters for different problems. To avoid parameter adjustment, a bio-inspired bare bones mayfly algorithm (BBMA) is proposed. The BBMA uses Gaussian distribution and Lévy flight, improves the convergence speed and solution accuracy, balance the exploration and exploitation of the algorithm. The minimum spanning tree (MST) problem is a classic combinatorial optimization problem. This paper gives a mathematical model for solving a variant of the MST problem in which all points and solution are on a sphere. Finally, the BBMA is used to solve the large-scale spherical MST problem, and the results are compared and analyzed with other well-known algorithms. Experimental results show that the proposed algorithm has better performance than other algorithms in solving spherical MST problem.