Beetle Swarm Optimization Algorithm:Theory and Application
This incremental improvement in optimization algorithms could benefit researchers and engineers in fields requiring efficient problem-solving, though it is not a foundational advance.
The authors introduced the beetle swarm optimization algorithm, a new meta-heuristic that enhances swarm optimization using beetle foraging principles, and demonstrated its superior performance on 23 benchmark functions and competitive results in engineering design problems like pressure vessel and Himmelblau optimization.
In this paper, a new meta-heuristic algorithm, called beetle swarm optimization algorithm, is proposed by enhancing the performance of swarm optimization through beetle foraging principles. The performance of 23 benchmark functions is tested and compared with widely used algorithms, including particle swarm optimization algorithm, genetic algorithm (GA) and grasshopper optimization algorithm . Numerical experiments show that the beetle swarm optimization algorithm outperforms its counterparts. Besides, to demonstrate the practical impact of the proposed algorithm, two classic engineering design problems, namely, pressure vessel design problem and himmelblaus optimization problem, are also considered and the proposed beetle swarm optimization algorithm is shown to be competitive in those applications.