# Multicriteria Decision Making and Its Application in Geothermal Power Project
## 2 Literature Review  
The application of an advanced Multicriteria Decision-Making Model to analyze issues related to renewable energy plant location selection is the current trend, using methods such as the AHP model, Best worst method (BWM), TOPSIS model, Evaluation Based on Distance from Average Solution (EDAS) model, and the categorical method. Complex decision-making problems are common in many industries and business sectors, and these problems usually have multiple types of criteria. Throughout the years, Multicriteria Decision-Making Models (MCDM) were developed to support decision makers in solving such complicated problems [7; 8; 9; 10; 11]. Decision-making problems are diverse, and include supplier selection [12; 13], service quality assessment [14; 15], financial risk assessment tool selection [16; 17], etc. Among these, MCDM models are frequently applied in facility location selection problems. [PERSON] et al. [18] developed a standardized MCDM-based approach for a water treatment plant location selection problem. The authors also developed a predictive model to automate the feasibility assessment process of potential locations. The authors' proposed approach was applied to a peri-urban city in northeastern India and the results were consistent with the real scenario. [PERSON] et al. [19] introduced a hybrid MCDM model based on FAHP, Data envelopment analysis (DEA), and TOPSIS methods to support the solar power plant location selection process under a vague decision-making environment. The author utilized several DEA models to identify the potential locations; then, a FAHP model was developed to calculate the weights of the selection criteria. Finally, the TOPSIS technique was applied to rank the potential locations according to their performance across the selection criteria. [PERSON] et al. [20] proposed an MCDM model to support a distribution center location process for agricultural supply chain. The proposed model was developed based on spherical fuzzy sets theory, AHP technique, and the combined compromise solution (CoCoSo) algorithm. A spherical FAHP model was deployed to calculate the location selection criteria weights, while a CoCoSo model was used to calculate the performance score and ranking of potential locations. The proposed model was applied to a realistic case study in the Mekong Delta Region of Vietnam to demonstrate its feasibility. [PERSON] and [PERSON] [21] developed an MCDM/A-based approach to the logistics center location selection problem. Their proposed approach utilized ELECTRE III/IV method to rank the potential regions according to their sustainability for placing the logistics center within their borders. The authors performed several computational experiments to demonstrate the approach's calculation process. [PERSON] et al. [22] introduced a two-stage fuzzy multiple attribute decision-making framework to support an offshore wind-PV-seawater pumped storage facility location selection process. The proposed framework was applied to a case study in China to validate the feasibility of the proposed framework. [PERSON] et al. [23] developed an MCDM model to support the international container intermodal hubs (ICIH) location selection process. The authors employed the GRA-TOPSIS method in combination with AHP, Entropy method, and game theory to build a decision support model. The proposed model was applied to identify an optimal location for ICHHs among 38 cities in China, and the result was compared with other popular MCDM models. There are multiple research works about the integration of MCDM models in facility location selections in the urban planning field. [PERSON] and [PERSON] [24] proposed an MCDM model based on the combination of Geographic Information System (GIS), AHP,and TOPSIS methods to support the earthquake risk assessment process in the city of Yalova in Turkey. The result of the model can be a reference for urban planners in disaster mitigation processes. [PERSON] et al. (2020) developed a GIS-based MCDM model for a landfill location selection problem.