Algorithm 1: Pseudo-Code of ESGA

Input: N, T, lb, ub, D. Initialize the population using Equation (1). FOR t = 1: T      Calculate the fitness value of the search agent using Equation (2).      Calculate the θ using Equation (14). //ASS      IF $\theta <\pi$      Calculate the $P_{wmean}^t$ and $Cov$ using Equations (16) and (17). //DGS           Update the individual’s position using Equations (3), (7), and (15).      ELSE           IF rand < 0.5                Update the individual’s position using Equation (18). //DSS           ELSE                Update the individual’s position using Equation (12).           END IF      END IF END FOR Output: The best position and the best fitness.