A modified gravitational search algorithm for continuous optimization
Emerson Hochsteiner de Vasconcelos Segundo, Gabriel Fiori Neto, Andre Mendes da Silva, Viviana Cocco Mariani, Leandro dos Santos Coelho · 2014
The gravitational search algorithm (GSA) is a stochastic population-based metaheuristic inspired by the interaction of masses via Newtonian gravity law. In this paper, we propose a modified GSA (MGSA) based on logarithm and Gaussian signals for enhancing the performance of standard GSA. To evaluate the performance of the proposed MGSA, well-known benchmark functions in the literature are optimized using the proposed MGSA, and provides comparisons with the standard GSA.