Joint decision-making for tanker deployment and refueling strategies under berthing time and fuel price uncertainties

This study proposes a robust optimization framework for the joint optimization of tanker deployment and refueling strategies under uncertainties in berthing times and fuel prices. Unlike traditional sequential approaches, the model jointly determines vessel assignment and refueling decisions within a unified mathematical formulation, explicitly accounting for interdependencies between operational variables. By incorporating robust optimization techniques, the framework addresses fuel price volatility and stochastic berthing delays, enabling resilient decision-making in dynamic maritime environments. Using real-world data from a leading maritime logistics provider, computational experiments demonstrate that the robust model reduces operational costs by 2.06% compared to deterministic approaches when fuel price fluctuations exceed critical thresholds (e.g., 300 RMB/ton for Heavy Fuel Oil (HFO) and 250 RMB/ton for Light Fuel Oil (LFO)). Sensitivity analyses further reveal the model’s resilience under extreme anchorage time uncertainties (e.g., 16-hour delays), achieving cost savings of up to 8.5%. The framework’s adaptability to diverse fleet configurations and regulatory environments underscores its practical value for enhancing decision-making in volatile markets.