Algorithm 2 DBAS Algorithm.

Objective Function: $F\left(X,\mathit{O}\right)$ DBAS Initialization: $\eta =0.99$ $d=0.9$ $d_1=0.9$ $d_2=0.9$ $\tau =0.9$ Portfolio Initialization: $T=iter$        %Iterations $D=pop$        %Total Portfolios $K=dim$        %No. of Stocks In Each Portfolio $X=\mathrm{randn}(D,K)$ $X_{\mathbf{best}}=X$ $\mathit{O}=[{\mathit{O}}_{\mathbf{1}},{\mathit{O}}_{\mathbf{2}},{\mathit{O}}_{\mathbf{3}},\cdots ,{\mathit{O}}_{\mathbf{K}}]$ % ${\mathit{O}}_K$ Includes Parameters For k-th Portfolio % ${\mathit{O}}_K=[M_K,{\mathbf{C}}_K]$$M_K:$ Mean ${\mathbf{C}}_K:$ Covariance ${\mathbf{P}}_{\mathbf{min}}=\mathit{F}\left(X,\mathbf{P}\right)$ $[G_{best},\mathrm{ind}]=\min (\mathit{F}\left(X,\mathbf{P}\right)$ ${\mathbf{S}}_{best}=X_{\mathrm{ind}}$ For$i=1:T$        $\mathbf{b}=\mathrm{randn}(D,K)$        $b_1=\mathrm{randn}(1,1)$        $b_2=\mathrm{randn}(1,1)$        $b_3=\mathrm{randn}(1,1)$        Compute $V$ using (36)        Compute $X_r$ and $X_l$ using (37) and (38)        Compute ${\mathit{F}}_r$ and ${\mathit{F}}_l$ suing (39) and (40)        Compute $X$ using (42)        For$j=1:D$               $F=F_j\left(X_{\mathbf{j}},{\mathit{O}}_{\mathbf{j}}\right)$               If$F<P_{min}^j:$                      $P_{min}^j=F$                      ${\mathbf{P}}_{best}^j=X_j$               End If                       End For                $[F,\mathrm{ind}]=\min \left(\mathit{F}\right(X,\mathit{O}\left)\right)$                If$F<G_{best}:$               $G_{best}=F$               ${\mathbf{s}}_{\mathbf{best}}=X_{\mathrm{ind}}$               ${\mathbf{S}}_{\mathbf{best}}=\mathrm{repmat}({\mathbf{s}}_{\mathbf{best}},D,1)$        End If        $r=$ rand        If$r<0.5:$               $d=\eta d+0.01$               $d_1=\eta d_1+0.01$               $d_2=\eta d_2+0.01$               $\tau =\eta \tau$        End If                End For