A Container Truck Appointment Scheduling Problem Considering Hydrogen Refueling and Soft Time Windows

Abstract

Rising maritime trade demand has exacerbated the challenges faced by drayage operators in inland container transportation. Drayage operators need to make precise truck scheduling decisions daily under truck appointments. Hydrogen-powered container trucks (HCTs) are promoted in container drayage, which brings further constraints for scheduling because of hydrogen refueling. A Mixed Integer Linear Programming (MILP) model for the container truck scheduling problem is proposed, which considers hydrogen refueling and soft time windows, aiming to minimize the total operational cost. To solve the proposed model, an improved Adaptive Large Neighborhood Search (ALNS) algorithm is designed, which is integrated with the Stochastic Local Search (SLS) and customized operators. Case studies demonstrate the eectiveness of the proposed model and algorithm. A novel perspective on container truck scheduling problems will be oered by the proposed model.