Multi-objective maintenance and rehabilitation decision-making modelling for highway networks: balancing economy, environment, and maintenance benefits

As China's highways transition from construction to maintenance, a 50% Maintenance and Rehabilitation (M&R) funding gap persists, and traditional top-down models fall short of refined demands. This study proposes a bottom-up multi-objective M&R decision-making framework for highway networks and defines Agency Cost (AC, M&R costs), User Cost (UC, expenses like fuel consumption and tire wear), Greenhouse Gas Emissions (GHGE, emissions from M&R and vehicle operations), and Benefits of Pavement Maintenance (BPM, integral function value of pavement performance improvement). The objectives are to minimise AC, UC, and GHGE, while maximising BPM. NSGA-III generates M&R solutions, and the entropy-weighted VIKOR method selects a compromise solution. The results reveal that UC decreases and BPM increases with AC, whereas GHGE exhibits a U-shaped relationship with AC. Traffic volume critically influences funding allocations, with high-traffic sections receiving proportionally larger funding and more frequent corrective measures as investments rise. This study provides a novel framework for refined M&R.