Gravitational Search Algorithm (GSA) is a recent stochastic search algorithm that is inspired from the concepts of gravity rule and law of motion in physics.
Despite its success and attractiveness, it has some coefficients and parameters that should be properly tuned to improve its performance. This paper studies
the performance of GSA by varying the parameters that controls its gravitational force. Then a new differential mutation operator is proposed to enhance
performance of GSA by accelerating its convergence. The proposed algorithm, namely DMGSA, is evaluated using 15 well-known benchmark functions from the special session of CEC2013 with different characteristics including randomly shifted optimum, rotation and non-separability.Etc...