# MILP-Based Approach for High-Altitude Region Pavement Maintenance Decision Optimization
## 5 Case Analysis
### Result Analysis
Additionally, since maintenance approaches with lower costs also result in lower carbon emissions (see Table 7), the results of Strategy 4 are very close to those of Strategy 2. Figure 2(c) further presents the carbon emissions of maintenance plans under different strategies. It can be seen that the carbon emissions for Strategy 1 are the highest, followed by Strategies 3 and 5, with Strategies 2 and 4 being the lowest. This result closely aligns with the conclusions in Figure 2(b), primarily because maintenance plans with lower carbon emissions also tend to have relatively lower costs (see Table 7). Strategy 4 aims solely to minimize carbon emissions, thus resulting in the most ideal carbon emission values. Figure 2(d),e shows the average PCI values and average IRI values under different strategies. A higher PCI value indicates a better pavement condition, while a lower IRI value also indicates a better pavement condition. From the two figures, it can be seen that the values corresponding to Strategy 1 are the most ideal, which is related to the strategy's primary focus on maintenance effectiveness. Meanwhile, the values corresponding to Strategies 2, 3, and 4 are relatively less ideal because their solutions tend to favor maintenance approaches that require lower costs and result in lower carbon emissions or shorter working hours. However, such maintenance approaches have a relatively smaller improvement effect on pavement conditions. As for Strategy 5, which considers maintenance effectiveness, the resulting values are relatively more ideal compared with Strategies 2, 3, and 4. Based on the above analysis, it can be observed that some decision objectives are interrelated, such as Strategy 4 focusing on minimizing carbon emissions and Strategy 2 focusing on minimizing maintenance costs. More importantly, Strategy 5 considers all objective functions simultaneously and achieves acceptable results across different indicators. This can be seen in Figure 2(a)-e where the corresponding values are all between the respective maximum and minimum values. Therefore, if multiple decision needs are considered simultaneously, Strategy 5 is an optional approach. Based on the results, compared with the Baseline strategy, Strategy 5 resulted in 19.698% less affected traffic volume, 2.651% less carbon emissions, 1.344% more maintenance costs, 1.260% less average PCI, and 3.864% more average IRI. Further analysis of Table 9 reveals that the Baseline strategy did not account for the impact of seasonal factors on the difficulty or suitability for maintenance, resulting in some maintenance tasks being scheduled during unsuitable months (e.g., Segments 1, 7, 12) and some segments being maintained during high-traffic months (e.g., Segment 5). Additionally, Table 9 shows that due to cost factors considered in the decision strategy, some segments with a good initial condition were allocated as \"no maintenance task\", while segments needing maintenance were assigned different maintenance approaches and scheduled in months with lower traffic volumes in different years, and these months were suitable for maintenance tasks. In summary, the model presented in this paper, especially the maintenance decision model based on Strategy 5, is more suitable for high-altitude regions. Combining Table 9 and the annual average daily traffic (AADT) of different segments, Figure 4 shows the correlation between traffic flow and PCI values, with a cubic fitting curve drawn. It can be seen that in the first year (2024), the curve is increasing, and the increasing trend is less pronounced in the second and third years, but still observable. This increasing trend indicates that segments with higher traffic flow tend to have higher PCI values. This result is related to the objective function \"maximize maintenance effectiveness\" included in Strategy 5, which aims for better pavement conditions on segments with higher traffic flow.