Abstract
To minimize grain fleet operational costs, we employ a route optimization approach that considers bunker costs. A mixed-integer programming model is created, factoring in the unique features of bulk grain shipping and varying oil prices at bunker ports. The goal is to optimize the fleet’s transportation route, with decision variables encompassing bunker port selection, bunker volume, and ship navigation path. Using a dry bulk cargo company’s grain transport fleet as a case study, the Gurobi solver validates the model’s effectiveness. Results reveal that, excluding the loading port, the grain fleet can select low oil price ports along the route for bunkering. Optimal cost reduction is achieved by choosing multiple bunker ports and increasing bunker quantity. Additionally, the model harmonizes port charges with bunker costs, refining the grain fleet’s transportation route and effectively managing operational expenses.
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