Optimizing alternative-fuel tugboat fleet towards decarbonization goals

As pivotal hubs in the global maritime supply chain, ports are under increasing pressure to decarbonize in response to tightening environmental regulations. Within port areas, heavy-duty tugboats, one of the main harbor craft, are major sources of port-area greenhouse gas emissions, yet systematic research for their decarbonization remains underdeveloped. Concurrently, growing global maritime traffic has amplified uncertainties in tugboat service demand, further complicating efforts to manage emissions. To address this gap, we develop a two-stage robust optimization model that determines an optimal tugboat fleet renewal plan considering six alternative fuels (biodiesel, liquefied natural gas, methanol, hydrogen, ammonia and electricity) under uncertain service demand and varying decarbonization targets. By integrating empirical operational performance, environmental impact, and economic viability, we aim to determine the fuel-mix renewal plan for the tugboat fleet that minimizes the fleet’s total costs, including capital costs, operational costs, and emission penalties. We employ an adapted column-and-constraint generation algorithm to solve this model. Through numerical experiments on real-world tugboat and vessel-call data from the Port of Singapore, our results reveal fuel-mix transition pathways aligned with different decarbonization milestones. We also quantify the influence of carbon prices on transitions in tugboat fuel types. The findings offer port authorities a decision-support tool for cost-effective, low-carbon, and operationally reliable planning for tugboat renewal.