Enhanced Gravitational Search Algorithm Based on Improved Convergence Strategy

Gravitational search algorithm (GSA) is one of the metaheuristic algorithms that has been popularly implemented in solving various optimization problems. The could perform better highly nonlinear and complex However, GSA also reported to have a weak local ability slow searching speed achieve its convergence. This research proposes two new parameters order improve GSA’s convergence strategy by improving exploration exploitation capabilities. are mass ratio distance parameters. parameter related strategy, while enhanced (eGSA). These expected create good balance between strategies eGSA. There seven benchmark functions tested on results shown eGSA able produce performance minimization fitness values execution times, compared with other variants. testing enhancements made successfully improved algorithm’s strategy. solution quality processing time. It be applied many fields solve problems efficiently.