Optimization of a Dual-fuel Engine Bunker Fuel Management Strategy

The maritime shipping industry is pivotal to global trade yet faces rising operational costs, particularly bunker fuel costs. This study develops an optimization framework that reformulates a real-world bunkering problem into a Mixed-Integer Quadratic Constraint Programming (MIQCP) formulation and solves it using the Gurobi Python API. Applied to an Asia-Africa liner shipping route, the model identifies an optimal bunkering strategy and selects 3 out of 14 ports. Furthermore, sensitivity analysis under varying fuel price scenarios provides robust insights into cost behavior.