A robust optimization approach for platooning of automated ground vehicles in port hinterland corridors

Modern ports face significant challenges as strategic nodes of global supply chains, being responsible for the coordination inbound and outbound flows at deep-sea in hinterland transport corridors. Digitization adoption disruptive technologies can help to tide over operational challenges. Automated Ground Vehicles (AGVs) are an integral part operations many modern ports, especially inside container terminals. With shift automated outside terminal areas, these AGVs may form platoons establish efficient port corridor. In this work, we propose a new robust optimization approach assess time cost-efficiency applying such AGV pickup delivery problem. We develop bi-objective mixed-integer programming model, which simultaneously minimizes cost elements, also considers emissions. Each transportation task be carried out by or conventional trucks, while number available vehicles each mode is uncertain (as they used connect different modalities transport). The model based on ellipsoidal uncertainty set handle augmented epsilon constraint method obtain Pareto-optimal solutions multi-objective developed framework evaluated two case studies: Port Rotterdam Netherlands Valparaíso Chile, with traveling distances corridors dry (200 km) pre-terminal (11 km), respectively. results indicate that direct scheme significantly more cost- time-efficient than benchmark provides low-carbon emission mode. While benefits decreased dwell times (56% average) carbon emissions (on average 10%) similar short long distances, savings increase (from 4.9% 8%) increased distance case.