Algorithm 1: Pseudocode of GSO Algorithm.

Initialization: m dimension Initialization: n glowworms Let s be step size Let $x_i\left(t\right)$ indicates the location of glow-worm t at time instant t Deploy agents in an arbitrary way $deploy-agent{s}_{–}randomly;$ for $i=1 \mathrm{to} n \mathrm{do} {\ell }_i\left(0\right)={\ell }_0$ $r_d^i\left(0\right)=r_0$ Consider highest number of iterations $= \max \_iter;$ assume $t=1;$ while $\left(t\le \max \_iter\right)$ do:   { for every glowworm i do ${\ell }_i\left(t\right)=\left(1-\rho \right)l_i\left(t-1\right)+\gamma Fitness \left(x_i\left(t\right)\right);$ for every glow-worm i do  { $N_i\left(t\right)=\{j:d_{ij}\left(t\right)<r_d^i\left(t\right);{\ell }_i\left(t\right)<{\ell }_j\left(t\right)\};$ for every glow-worm $j\in N_i\left(t\right)$ do: $p_{ij}\left(t\right)=\frac{{\ell }_j\left(t\right)-{\ell }_i\left(t\right)}{\Sigma p\in N_i\left(t\right){\ell }_p\left(t\right)-{\ell }_i\left(t\right)};$ $j=select\_glowworm\left(\overrightarrow{p}\right);$ $x_i\left(t+1\right)=x_i\left(t\right)+step\left(\frac{x_j\left(t\right)-x_i\left(t\right)}{\Vert x_j\left(t\right)-x_i\left(t\right)\Vert }\right)$ $r_d^i\left(t+1\right)=\min \left\{r_{sy}, \mathrm{maximumm} \left\{0, r_d^i\left(t\right)+\beta \left(n_t-\left|N_i\left(t\right)\right|\right)\right\}\right\};$  } $t\leftarrow t+1;$   }