Integrated optimization of rural passenger-freight transport with leasing cost uncertainty: A robust location-routing framework

Operational challenges and high costs impede rural logistics in China. This study proposes a novel integrated passenger-freight-postal (PFP) system that synergizes fixed-route buses with logistics vehicles for efficient last-mile delivery. The core innovation lies in a collaborative replenishment mechanism: logistics vehicles deliver goods to service stations, which subsequently resupply buses during transit, thereby enabling buses to utilize otherwise idle cargo capacity. An optimization model for the Service Station Location-Routing Problem on fixed bus networks for PFP systems (SSLRP-PFP) is developed to jointly determine station locations, bus route utilization, and vehicle routing. To address the critical volatility of station leasing costs, a robust optimization extension is formulated. An efficient tailored metaheuristic (MCWIGALNS, integrating Modified Clarke-Wright, Iterated Greedy and Adaptive Large Neighborhood Search) is designed for solution. Grounded in rural China’s operational realities, the approach is validated through computational experiments and a case study in Neixiang County. Results demonstrate reduced total costs, improved delivery efficiency, and robust performance under cost uncertainty. This work provides a practical decision-making framework for sustainable rural logistics by leveraging existing transit assets and explicitly modeling operational and financial uncertainties.