Algorithm 1. Particle Swarm Optimization Procedure

Input: Objective function $f\left(x\right)$, number of particles $N$, dimension $D$, inertia weight $\omega$, acceleration coefficients $c1$, $c2$, max iterations $T_{max}$     Initialize particle positions $x_i \in R^D$ and velocities $v_i\in R^D$ for $i$= 1 to $N$     Initialize personal bests $p_{best}\leftarrow x_i$, evaluate $f\left(p_{besti}\right)$        Set $g_{best}\leftarrow {argmin}_i·f\left(p_{besti}\right)$ For $t = 1$ to $T_{max}$ DO   For $i = 1$ to $N$   DO         Update velocity $v_i\leftarrow \omega \ast v_i+c_1\ast rand\ast \left(p_{besti}-x_i\right)+c_2\ast rand\ast \left(g_{besti}-x_i\right)$         Update position $x_i \leftarrow x_i + v_i$         Evaluate fitness $f\left(x_i\right)$         If $f\left(x_i\right) < f\left(p_{besti}\right)$ then           $p_{besti} \leftarrow x_i$         If $f\left(p_{besti}\right) < f\left(g_{best}\right)$ then            $g_{best} \leftarrow p_{besti}$         END IF      END IF    END FOR   END FOR return $g_{best}$, $f\left(g_{best}\right)$ Output: Global best position $g_{best}$ and value $f\left(g_{best}\right)$