A multiobjective maintenance and rehabilitation decision-making method for highway networks

Pavement maintenance and rehabilitation planning is of great significance to maintaining the level of road use, ensuring vehicle driving safety, and optimizing the use of maintenance funds. However, highway network maintenance has problems such as reliance on traditional experience judgment and single decision-making indicators, which may lead to unreasonable allocation of maintenance resources, poor maintenance effect, high cost, and large amount of carbon emissions, thus exacerbating the negative impact on the environment. Therefore, this study proposes to use the genetic algorithm to comprehensively consider the maintenance cost and carbon emissions of the maintenance process, aiming to improve the efficiency of capital utilization, ensure the pavement use condition, and minimize the impact on the environment. In addition, this study conducted a case analysis of the highway network in a state in the United States, and different maintenance plans can be formulated according to the requirements of budget and carbon emissions. The results show that the genetic algorithm under multi-objective decision-making is effective and reliable for promoting sustainable pavement maintenance. This study provides an effective solution for the formulation of pavement maintenance strategies, which takes into account environmental sustainability while controlling the budget and ensuring pavement use.