###### Abstract
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **The proposed Methods** &
\begin{tabular}{c} **Studied Power** \\ **Systems** \\ \end{tabular} & **Objectives** \\ \hline
[22] & \begin{tabular}{c} Modified moth swarm \\ algorithm (MMSA) \\ \end{tabular} & \
\begin{tabular}{c} Modified IEEE-30 and \\ IEEE-118 bus test \\ systems \\ systems \\ \end{tabular} &
\begin{tabular}{c} Total fuel costs considering \\ renewable energy sources \\ (RES), power losses, voltage \\ deviation \\ \end{tabular} \\ \hline
[23] & \begin{tabular}{c} A hybrid of a \\ non-dominated sorting \\ genetic algorithm-II \\ (NSGA-II) and fuzzy \\ satisfaction-maximizing \\ method \\ \end{tabular} & \
\begin{tabular}{c} Modified IEEE 30 and \\ 300 bus systems \\ \end{tabular} &
\begin{tabular}{c} Multi-objective dynamic OPF \\ (MDOPF) considering wind \\ generation (WG) and \\ demand response (DR) with \\ fuel cost, carbon emission \\ and active power losses \\ \end{tabular} \\ \hline
[24] & \begin{tabular}{c} Multi-objective \\ glowworm swarm \\ optimization (MOGSO) \\ \end{tabular} & \
\begin{tabular}{c} Modified IEEE 30 and \\ 300 bus systems \\ \end{tabular} &
\begin{tabular}{c} Total generation cost, \\ transmission losses, and \\ voltage stability \\ enhancement index \\ \end{tabular} \\ \hline
[25] & \begin{tabular}{c} Bird swarm algorithm \\ (BSA) \\ \end{tabular} & \
\begin{tabular}{c} IEEE 30 bus system \\ \end{tabular} &
\begin{tabular}{c} Total fuel costs and emissions \\ \end{tabular} \\ \hline
[26] & \begin{tabular}{c} Multi-objective PSO \\ (MOPSO) \\ \end{tabular} & \
\begin{tabular}{c} IEEE 30-bus and IEEE \\ 57-bus systems \\ \end{tabular} &
\begin{tabular}{c} Generation cost, transmission \\ loss, and the maximum \\ voltage collapse proximity \\ index (VCPI) \\ \end{tabular} \\ \hline
[27] & \begin{tabular}{c} Modified strength Pareto \\ evolutionary algorithm \\ \end{tabular} & \
\begin{tabular}{c} IEEE 30-bus and IEEE \\ 57-bus systems \\ \end{tabular} &
\begin{tabular}{c} Fuel cost and emission \\ \end{tabular} \\ \hline
[28] & \begin{tabular}{c} Ant lion optimization \\ (ALO) \\ \end{tabular} & \
\begin{tabular}{c} Modified IEEE 30 bus \\ system \\ \end{tabular} &
\begin{tabular}{c} Operational costs, voltage \\ profile, and system-wide \\ transmission power losses \\ \end{tabular} \\ \hline
[29] & \begin{tabular}{c} Modified Jaya \\ 118-bus systems \\ \end{tabular} & \
\begin{tabular}{c} IEEE 30-bus and IEEE \\ 118-bus systems \\ \end{tabular} &
\begin{tabular}{c} Operational costs, emission, \\ power loss and voltage \\ profile improvement \\ \end{tabular} \\ \hline
[30] & \begin{tabular}{c} Improved salp swarm \\ algorithm (ISSA) in \\ compared with \\ moth-flame optimization \\ (MFO), improved \\ harmony search (IHS), \\ genetic algorithm (GA) \\ \end{tabular} & \
\begin{tabular}{c} \\ IEEE 30-bus, IEEE \\ 57-bus and IEEE \\ 118-bus systems \\ \end{tabular} &
\begin{tabular}{c} Minimize quadratic fuel cost, \\ piecewise and quadratic fuel \\ cost, considering the \\ valve-point effect and \\ prohibited zones. \\ \end{tabular} \\ \hline
[31] & \begin{tabular}{c} Developed GWO \\ (DGWO) \\ \end{tabular} & \
\begin{tabular}{c} IEEE 30 bus system \\ \end{tabular} &
\begin{tabular}{c} Quadratic fuel cost \\ minimization, piecewise \\ quadratic cost minimization, \\ and quadratic fuel cost \\ minimization considering the \\ valve point effect. \\ \end{tabular} \\ \hline
[32] & \begin{tabular}{c} Sime mould algorithm \\ (SMA) in compared with \\ gorilla troops optimizer \\ (GTO), orca predation \\ algorithm (OPA), \\ artificial ecosystem \\ optimizer (AEO), hunger \\ games search (HGS), \\ jellyfish search (JS) \\ optimizer, and \\ success-history-based \\ parameter adaptation for \\ DE. \\ \end{tabular} & \
\begin{tabular}{c} \\ IEEE 30-bus test \\ system and Algerian \\ power system, DZA \\ 114-bus \\ \end{tabular} &
\begin{tabular}{c} The overall cost of the \\ system, including reserve \\ cost for over-estimation and \\ penalty cost for \\ under-estimation of both \\ PV-solar and wind energy. \\ \end{tabular} \\ \hline \end{tabular}
\end{table}