Optimizing bunkering and sailing strategies for sustainable shipping: a decision model for reducing costs and carbon emissions

Bunkering costs constitute the largest portion of operational expenses in the shipping industry, directly influencing both economic efficiency and environmental impact. In line with Sustainable Development Goals (SDGs) 12 and 13, this study develops a decision model that jointly optimizes bunkering and sailing speed in liner shipping, with the aim of minimizing fuel costs and reducing carbon emissions. The model explicitly incorporates two often-overlooked aspects of the bunkering process: the requirement for empty tanks before refueling and the fuel inspection process. Due to the presence of infinite-dimensional and nonlinear terms, solving the model is computationally challenging. To address this complexity, we employ approximation algorithms and linearization techniques to transform the model into a mixed-integer linear programming (MILP) formulation. Additionally, we implement a Branch-and-Cut algorithm to enhance computational efficiency. Numerical experiments are conducted to evaluate the model’s performance, along with sensitivity analyses to assess the impact of key parameters. The results demonstrate that both the empty tank requirement and fuel inspection significantly influence bunkering decisions and sailing strategies, with the latter having a more pronounced effect. Moreover, our findings highlight the potential for sustainable fuel management practices to contribute to carbon reduction in maritime transportation. This study provides valuable insights for policymakers and industry stakeholders seeking to balance cost efficiency and environmental sustainability in shipping operations.