## 2 Related Works
\begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Focus** & **Applied Model** & **Results** & **Limitations** \\ \hline \multirow{3}{*}{[21]} & Multi-criterion optimization for distribution networks in supply chains & GA integrated with Analytic Hierarchy Process (AHP) & Enhanced decision-making with better balance between cost, efficiency, and service levels. & May require extensive computational resources for large-scale problems. \\ \hline \multirow{3}{*}{[23]} & Job scheduling in computational Grids considering multiple criteria & AGA and AGA with Overhead (AGAwoO) & Superior performance across multiple criteria for energy efficiency and security. & High computational demands; overhead considerations for real-time applications. \\ \hline \multirow{3}{*}{[25]} & Electrical distribution system optimization using Pareto fronts & GA with AHP and TOPSIS for decision-making for decision-making for target networks. & Effective multi-objective optimization with scalable applications to microgrids and larger networks. & Results dependent on the selection of criteria weighting and operator tuning. \\ \hline \multirow{3}{*}{[27]} & Planning of distributed energy systems with multi-criteria evaluation & \(\epsilon\)-constraint optimization with AHP and Gray Relation Analysis & Comprehensive framework integrating optimization and evaluation for diverse scenarios. & Complex model setup; reliance on accurate input data for optimization. \\ \hline \multirow{3}{*}{[29]} & Optimization of distributed energy systems in commercial buildings & GA & Identified optimal strategies for energy and CO2 reductions, tailored by building types. & Context-specific findings may not generalize to non-commercial settings. \\ \hline \multirow{3}{*}{[30]} & Logistics performance evaluation using MCDM techniques & GA for criteria weighting with GA outperforming traditional methods. & More accurate logistics rankings and frequent evaluations with GA outperforming traditional methods. & Limited to the Logistics Performance Index framework; model effectiveness depends on input data quality. \\ \hline \multirow{3}{*}{[31]} & Framework for Distributed Multi-Energy Systems (DMES) & GA with Maximum Rectangle Method & Enhanced DMES performance with tailored operation strategies like Following Electrical Load (FEL). & Performance influenced by load uncertainties and market conditions. \\ \hline \multirow{3}{*}{[32]} & Hybrid energy system for electricity and desalination & GA and ANN & Improved efficiencies and reduced costs; path to sustainable energy and water production. & System performance depends on optimal parameter selection and operational stability. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of MCDM approaches using GAs. The building sector, as a significant energy consumer, requires a transition to cleaner energy systems. A Distributed Multi-Energy System (DMES) integrates renewable energy and storage solutions. [PERSON] et al. [31] propose a framework which includes a Maximum Rectangle Method and GAs for capacity optimization and operational strategy design. The evaluation combines the Analytic Hierarchy Process, Entropy Weight Method, and Set Pair Analysis. Performance analysis of the DMES in various scenarios, such as energy prices and load uncertainties, highlights its superiority over alternatives. Optimal operation strategies like Following Electrical Load (FEL) enhance DMES performance. Recommendations include increasing renewable energy integration and improving load forecasting. The findings offer valuable guidance for sustainable energy applications in buildings. [PERSON] et al. [32] explore an innovative hybrid energy system that integrates flame-assisted fuel cells and a multi-effect desalination process to produce electricity and potable water efficiently and affordably. Using advanced modeling through the Engineering Equation Solver (EES), the system's performance is analyzed in terms of energy, exergy, economics, and environmental sustainability.