# Airport pavement Maintenance Decision-Making System with Condition Cases Optimization
## 2 Airport Pavement Management System Architecture
### Decision Making Process for Airport Pavement Management System
#### 2.4.2 Benefit  
User benefits for benefit-to-cost (B/C) analysis are defined as shown in Equation (5). The most common method for calculation is the area under the pavement condition curve  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Category**} & \multirow{2}{*}{**Alternatives**} & \multirow{2}{*}{\
\begin{tabular}{c} **Unit Cost** \\ **(USD/m2)** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **SL after** \\ **Implementation** \\ \end{tabular} } & \multicolumn{3}{c}{**Life Extension (Year)**} \\ \cline{3-6}  & & & **1 st** & **2 nd** & **3 rd** \\ \hline Reconstruction & Reconstruction & 105.75 & 100 & 30 & - & - \\ Major & 15 cm M/OL * & 78.96 & & 10 & 6 & 4 \\ Rehabilitation & 7.5 cm M/OL * & 56.40 & 95 & 8 & 4.8 & 3.2 \\  & 5 cm M/OL * & 47.00 & & 5 & 3 & 2 \\  & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\  & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\ Preventive & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\ Maintenance & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\  & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\  & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\ \hline \hline \end{tabular}  
* M/OL = milling and overlay.  
\end{table}
Table 1: Cost and effect of the M&R methods used in the analysis.  
(AUC) between the PCI, international roughness index (IRI), and the threshold scores [36]. In this paper, we considered the delay effects due to traffic closure, specifically applying it to the reconstruction maintenance method among the three maintenance method categories. Based on domestic experience, especially in airports with high traffic volumes, unit costs for minimizing traffic closure times were 2.4 times higher for pre-cast methods and 3.5 times higher for rapid-setting methods, compared with 7.5 cm milling and overlay [24]. User benefits due to preventing traffic closure were calculated at USD 670/m\({}^{2}\) compared with partial repairs.  
\[B=\lambda*AUC-(1-\lambda)*delay\ cost \tag{5}\]  
where AUC = area under curve and \(\lambda\) = factor on number of runways and traffic volume.  
The traffic volume groups were categorized as high, medium, and low groups, based on the number of annual departures in equivalent B737-900 ER aircraft. The distribution of airport groups in South Korea was 23% for high traffic, 62% for medium traffic, and 15% for low traffic. The \(\lambda\) coefficient was determined based on the traffic volume group and the number of runways (Table 2). As \(\lambda\) increased, the importance of method application became higher compared with closure effects. The highest \(\lambda\) values were observed in the C traffic group and when there were three or more runways. Conversely, under opposite conditions, the reduction in the closure effect was most significant, with the most extreme case being when traffic was high and there was only one runway.