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\documentclass[journal]{IEEEtran}
\usepackage[classicReIm]{kpfonts}
\usepackage{booktabs,tabularx,lipsum}
\usepackage{longtable}
\usepackage{float}
\usepackage{graphicx}
\usepackage{subfigure}
\usepackage{multirow}
\usepackage{url}
\usepackage{algpseudocode}
\begin{document}
\begin{algorithm}[H]
    \caption{EDE.}
    \label{pseudoEDE}

         Parameters initialization ${Maximum_iter, {R_c}, POPLAT, and h}$\;
        Population generation using Equation (\ref{eq:7}) \;
        \For {h = 1:H}
         {
         Compute mutant vector using Equation (\ref{eq:8})\;
        \For{iter= 1:Maximum_iter}
        { Compute first trial vector with {R_c} 0.3\;
        \If {$rand() \leq 0.3$}
         {$\mu_{j}=m_{j}$\\
         else\\
        {$\mu_{j}=v_{j}$}
    }


         Compute second trial vector with CR 0.6\;
        \If {$rand() \leq 0.6$}
        { $\mu_{j}=m_{j}$\\
        else\\
        { $\mu_{j}=v_{j}$ }
    }

        Compute third trial vector with CR 0.9\;
        \If {$rand() \leq 0.9$}
        {$\mu_{j}=m_{j}$\\
        else\\
        {$\mu_{j}=v_{j}$}
    }

        Create $4^{th}$ and $5^{th}$ trial vector using Equations (\ref{4_trial}) and (\ref{5_trial})\;
        Find out trial vector which is best \;
        $P_{new} \gets$ best of $ \mu_{j}$ \;
        Compare trial vector with target vector\;
        \If {$f({P_{new}}) < f (P_{j})$}
        {$P_{j} = P_{new}$}
    }
}
\end{algorithm}
\end{document}