Carbon Dioxide Minimization in Large-Scale Pavement Network Maintenance Planning

Choosing an appropriate strategy to maintain pavements has become a significant concern. Recently, pavement agencies tackle large-scale networks, which makes the problem complicated. To prevail in this complexity, utilizing metaheuristic algorithms can be an ideal approach. By increasing the dimension of the problem, the competency of metaheuristic algorithms is by far enhanced. To this end, the water cycle algorithm is applied to solve the problem. In this investigation, two models, including single objective optimization and multi-objective optimization, are taken into consideration. In the single-objective model, the minimization of the network International Roughness Index (IRI) is considered as the objective function. In multi-objective optimization modeling, minimization of the network International Roughness Index and embodied CO2 emission are taken into account simultaneously. Furthermore, a new constraint is considered in the model, which leads to restricting the budget fluctuation in different years of the analysis period. A network, including 79 segments, is the case study of this investigation. The results reveal that the water cycle algorithm is highly qualified to solve the pavement maintenance and rehabilitation problem. According to the results, multi-objective optimization reduces the CO2 emission by 47.2% compared with single-objective modeling. Furthermore, the variation of minimum and maximum costs is less than 20% in the planning horizon.