Energy-aware scheduling and berth allocation for ferries under phased cold ironing upgrades

Many ferry ports are undergoing a phased transition from fully diesel-powered vessels to hybrid ferries capable of connecting to shore power while berthing. This transition raises new operational challenges: when several hybrid ferries arrive simultaneously, limited cold ironing capacity may force some vessels to revert to auxiliary diesel engines, undermining scheduling efficiency and resource use. To address this issue, we develop a tri-objective mixed-integer programming model for energy-aware ferry scheduling and berth allocation. The model jointly minimises vessel-related CO2 emissions, reduces grid capacity exceedances that constrain port operations and energy storage, and improves berth utilisation. It captures key logistical and operational complexities of ferry ports, including tightly coupled ferry schedules and berth availability driven by short sea crossings with predictable arrival times, berth-vessel compatibility constraints across multiple operators, and immediate berthing requirements, thereby necessitating an integrated berth allocation and scheduling model. Using empirical data from a major Western European ferry port, our computational experiments demonstrate that the proposed approach can reduce berthing-related CO2 emissions by up to 70% depending on demand patterns and fleet composition. From the perspective of ferry operators, total daily emissions across crossings and berthings decline by 5–9% as hybrid adoption increases. Even in the absence of hybrid vessels, the model identifies opportunities to cut emissions by 12–40% compared with business-as-usual scheduling through more efficient utilisation of berth capacity. The results highlight how integrated berth allocation and energy-aware scheduling, framed as a logistics optimisation problem, can deliver both operational efficiencies and substantial environmental benefits, offering ports a practical pathway to manage the hybrid transition without immediate large-scale infrastructure expansion.