# A Soft Computing Framework to Support Consumers in Obtaining Sustainable Appliances from the Market
## 3 Material & Research Method
### Proposed Approach  
The method presented in this work has been designed to support a consumer who intends to purchase, from the market, a set of appliances for their household (Figure 1). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Emission Factor (gCO2/kWh)** & **675.00** & **Discount Factor (\%)** & **7.00** \\ \hline Lifecycle (usage phase) (years): & 10.00 & Annual Factor & 7.03 \\ Electrical Energy tariff (\(\tau_{ELuct}\)) (€/kWh) & 0.16 & Water tariff (\(\tau_{H_{2}O}\)) (€/m\({}^{3}\)) & 1.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Emission factor and other assumptions considered in this work. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Energy Service** & \multicolumn{4}{c}{**Hours**} \\ \cline{2-5}  & **Day** & **Week** & **Month** & **Year** \\ \hline Dryer machine & 1.5 & 4.0 & 15.0 & 183.0 \\ \hline Washing machine & 1.2 & 4.3 & 16.0 & 189.0 \\ \hline Fridge/freezer & 11.0 & 76.3 & 329.1 & 4007.0 \\ \hline Oven (electric) & 1.1 & 1.9 & 8.0 & 97.0 \\ \hline Dishwasher machine & 1.0 & 4.1 & 16.0 & 193.0 \\ \hline Air conditioning & 2.1 & 12.1 & 47.0 & 587.0 \\ \hline Lighting & 5.0 & 35.2 & 150.1 & 1823.0 \\ \hline \hline \multirow{2}{*}{**Energy Service**} & \multicolumn{4}{c}{**Usage Frequency**} \\ \cline{2-5}  & **Day** & **Week** & **Month** & **Year** \\ \hline Dryer machine & 1 & 3 & 14 & 185 \\ \hline Washing machine & 1 & 2 & 14 & 181 \\ \hline Fridge/freezer & 1 & 6 & 28 & 359 \\ \hline Oven (electric) & 1 & 2 & 7 & 94 \\ \hline Dishwasher machine & 1 & 3 & 14 & 189 \\ \hline Air conditioning & 1 & 4 & 22 & 276 \\ \hline Lighting & 1 & 6 & 28 & 359 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Consumer usage profile (considered). This set is formed by individual solutions regarding each energy service to be acquired and is obtained from a group of candidate solutions previously selected using MAVT according to the consumer's preferences, needs and concerns, and regarding each sustainability dimension (Figure 1). Such an approach can be better described through a detailed view, as presented in Figure 2. The first phase starts with pre-selection of a set of potential solutions \(\left(x_{ij}\right)\) from the market and based on specific criteria. Although the corresponding attributes/criteria remain the same, the corresponding values vary according to the number of occupants. The adopted criteria used here allows for the pre-selection of household appliances available in the market, so the decision space can be reduced by considering only these options that are adjusted to the consumer needs as well as through increasing the efficiency of NSGAII by acquiring optimal and feasible solutions within less time. According to Figure 2, the first stage starts with the pre-selection of a set of candidate solutions \(\left(x_{ij}\right)\), existing in the market, which are based on specific criteria and according to the number of occupants of the building. Regarding the adopted criteria, it is the same, with the corresponding attribute' values varying based on the occupant number. An example of such criteria, considering the case studied in this work, is shown on Table 1.  
Therefore, each candidate solution \(\left(x_{ij}\right)\) is then considered as an option \(i\) related to household appliance type \(j\), to be bought from the market by the consumer. By considering a consumer's profile, (e.g., Table 2), the approach involves performing a lifecycle cost assessment (LCCA) regarding each household appliance in order to calculate the respective savings as regarding energy consumption \(\left(S_{E.Cons_{ij}}\left(x_{ij}\right)\right)\), water consumption \(\left(S_{H2O,Cons_{ij}}\left(x_{ij}\right)\right)\), and the initial investment \(\left(S_{inv_{ij}}\left(x_{ij}\right)\right)\). The equivalent CO\({}_{2}\) emissions were then calculated according to [26]. All of the parameters mentioned above, are savings, and they result from the comparison of the efficient and the related standard solution (less sustainable one).