## 2 Literature Review
Their research considered the Total Energy Consumption (TEC) and the Life Cycle Cost (LCC). [PERSON] et al. [20] developed and tested a multiple-criteria decision support system that assists with the choice of refurbishment technologies by assessing the alternatives for the achievement of Near Zero Energy Building (NZEB) targets. [PERSON] et al. [29] proposed a methodology for decision support in the selection of low-carbon refurbishment solutions for apartment blocks in subtropical cities with CO2 emissions and energy consumption considered. [PERSON] et al. [30] used a multi-criteria approach for residential building retrofitting based on life cycle assessment. [PERSON] et al. [28] applied multi-attribute decision support for achieving near zero-energy buildings, where indoor conditions and energy consumption were considered. [PERSON] and [PERSON] [16] developed an intelligent decision support system for energy retrofitting (ERIDS) to support homeowners. This system integrates expert knowledge with quantitative information obtained by using the Delphi method. It includes five knowledge-based modules covering lighting, energy saving and stand-alone measures, heating, cooling, and air conditioning, thermal envelope, and hot water heating, as well as installation solutions. Other authors have developed sustainable renovation methodologies that integrate the three most important dimensions of sustainability and usually are based on multiple-criteria assessment methods. [PERSON] et al. proposed a multiple-criteria decision support method to assist with the selection of sustainable and feasible strategies for housing renovation [21]. Both methods and systems were tested in Sweden. [PERSON] and [PERSON] [14] used pairwise comparison and TOPSIS methods to develop a multiple-criteria framework for decision making related to the renovation of residential buildings. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Authors** &
\begin{tabular}{c} **Proposed** \\ **Methods/Systems/Tools** \\ \end{tabular} & **Criteria** & **Methods** \\ \hline \multirow{3}{*}{[PERSON] et al. [28]} & Multi-attribute decision & Energy consumption, indoor & \multirow{3}{*}{TOPSIS, ARAS WASPAS} \\  & support for achieving nearly & environment & \\  & zero-energy buildings & & \\ \hline \multirow{3}{*}{[PERSON] et al. [29]} & Tool that helps make decisions & \multirow{3}{*}{CO2 emissions and energy} & \multirow{3}{*}{No particular method} \\  & on the choice of refurbishment & & \\ \cline{1-1}  & solutions focused on low & & \\ \cline{1-1}  & carbon for apartment blocks & & \\ \cline{1-1}  & in subtropical cities & & \\ \hline \multirow{3}{*}{[PERSON] et al. [30]} & Multiple-criteria approach to & \multirow{3}{*}{Life cycle assessment} & Pareto front \\  & retrofit residential buildings & & \\ \hline \multirow{3}{*}{[PERSON] et al. [31]} & Decision matrix methodology & \multirow{3}{*}{Economic and environmental} & \multirow{3}{*}{Pareto front, matrix} \\  & for retrofitting techniques of & & \\ \cline{1-1}  & existing buildings & & \\ \hline \multirow{3}{*}{[PERSON] et al. [32]} & Environmental and economic & \multirow{3}{*}{Environmental and economic} & \multirow{3}{*}{TOPSIS} \\ \cline{1-1}  & analysis based on scenarios & & \\ \cline{1-1}  & for clean energy incentives in & & \\ \cline{1-1}  & homes & & \\ \hline \multirow{3}{*}{[PERSON] et al. [33]} & Support for decisions on & \multirow{3}{*}{Thermal comfort, economic} & \multirow{3}{*}{Genetic algorithm} \\ \cline{1-1}  & building envelope retrofitting & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._The basis of this framework was a hierarchically structured system of economic, social and environmental criteria; two case studies conducted in Spain and related to a five-story building were used to test the framework. The simplified 'holistic sustainability decision-making support framework' developed by [PERSON] et al. [18] can assist in all project stages related to building renovation.