E. H. V. Segundo, Gabriel Fiori Neto, A. M. D. Silva, V. Mariani, L. Coelho
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A modified gravitational search algorithm for continuous optimization
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.
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