Gravitational Search Algorithm With Hierarchical Structure Guided By Elite Individual
Haotian Li, Yifei Yang, Haichuan Yang, Zheng Tang, Shangce Gao · 2022
The Gravitational Search Algorithm (GSA) is a Newtonian gravity-based meta-heuristic algorithm. The algorithm updates population members’ locations according to the gravitational pull between them in order to solve the optimization issue. However, in some cases, the convergence of the algorithm is not fast enough. In order to improve the convergence speed of the algorithm while alleviating the problem of easily falling into local optima, we propose a gravitational search algorithm with hierarchical structure (EHGSA) guided by elite individuals. This structure can help the algorithm to have the ability to jump out of the local optimum while improving the convergence speed. The effectiveness of the proposed algorithm EHGSA is validated using the IEEE CEC2017 benchmark function test set of 29 functions.