Numerical analysis of a multi-objective maintenance decision-making model for sustainable highway networks: Integrating the GDE3 method, LCA and LCCA.

• A innovative and efficient model was proposed for multi-lane highway. • The learning was collected a lot of existed pavement segments and built a large-scale highway network. • The LCA and LCCA was integrated to assess the sustainability of the M&R decision. • GDE3 performs well in selecting more cost-effective M&R optimization. A pavement maintenance and rehabilitation decision-making model plays a significant role in the sustainable development of highway networks. However, various maintenance and rehabilitation models lack the capacity to provide multi-objective maintenance decision-making strategies, which are solely concerned with reducing maintenance costs. This study aims to propose a multi-objective maintenance decision-making model, called the Pavement Maintenance-Generalized Differential Evolution 3 (called PM-GDE3), by integrating the pavement condition indices and the generalized differential evolution 3 (GDE3) method. Economic aspect, pavement sustainability, and environmental dimensions were considered in the proposed model to increase the flexibility of pavement management. In this study, the widely-used PAVER maintenance system,which represents a conventional M&R decision-making model and the PM-GDE3 model were applied to estimate the optimal maintenance and rehabilitation schedules for the highway networks, and the results from these models were compared. The results show that the maintenance strategy obtained from the PM-GDE3 model maintains the highway in an acceptable condition. In addition, it has been found that the PM-GDE3 model saves 30.9% of maintenance expenses, about 169 million CNY, 16.9% of carbon emissions, around 4,469 kt, and 11.6% of energy consumption, 2.8GJ, for as long as 30 service years compared to the PAVER model. The PM-GDE3 model outperforms the widely used PAVER maintenance system due to its capacity to propose the optimal solution by establishing a real-time simulation with numerous pavement conditions after maintenance application. This field is the first attempt to combine pavement performance prediction model, life cycle assessment method and life cycle cost assessment. The achievements of the paper are expected to combat the impending energy crisis and climate change impacts of pavement maintenance and rehabilitation. [ABSTRACT FROM AUTHOR]