Dual-Objective Optimization of Port Tugboat Scheduling with Heterogeneous Service Capabilities

As critical hubs in the global supply chain, a port’s competitiveness and sustainability are directly impacted by the efficiency and carbon emissions of its tugboat scheduling. This paper addresses the scheduling optimization of heterogeneous tugboat fleets, aiming to balance these dual objectives. A Mixed-Integer Linear Programming (MILP) model is constructed to minimize vessel waiting time and total carbon emissions, considering key real-world constraints such as tidal windows and channel capacity. Given the model’s complexity, an improved multi-objective evolutionary algorithm is designed, which significantly enhances the performance for solving large-scale instances. A case study based on actual data from Xiamen Port shows that the proposed model and algorithm can effectively generate a series of Pareto-optimal schedules, providing a decision-making basis for port authorities to achieve green and efficient tugboat scheduling.