Optimizing speed, routing, and refueling strategy are three ways to reduce ship operating costs without modifying on ship. Most past studies have simultaneously optimized one or two variables, resulting in a local optimal solution. To limit sulfur emissions, some governments have established Emission Control Areas (ECAs) in recent years, where ships must use low sulphur fuels. The constraints created by ECAs makes the simultaneous optimization of the three variables even more challenging. This study developed a nonlinear mixed integer programming model to address the challenge of simultaneously optimizing the three variables. After transforming the nonlinear discrete mixed integer programming model into a convex nonlinear continuous programming model, the study proposed a solution algorithm for the proposed model. The new model in this study was applied to the Europe-United States (US) and Southeast Asia service route. The results show that the optimal refueling policy, route, and speed selection can be determined simultaneously using the proposed model and solution method. The study investigated the impact of fuel price on ship refueling strategy, route, and speed; and developed insights from the example analyses.

优化速度，航线和加油策略是在不进行船上修改的情况下降低船舶运营成本的三种方法。过去的大多数研究同时优化了一个或两个变量，从而产生了局部最优解。为了限制硫排放，近年来，一些政府建立了排放控制区（ECA），在该区船必须使用低硫燃料。ECA创建的约束条件使得同时优化三个变量更具挑战性。这项研究开发了一种非线性混合整数规划模型，以解决同时优化三个变量的挑战。将非线性离散混合整数规划模型转换为凸非线性连续规划模型后，研究提出了一种求解算法。本研究中的新模型已应用于欧美（美国）和东南亚航线。结果表明，使用所提出的模型和求解方法可以同时确定最佳加油策略，路线和速度选择。该研究调查了燃油价格对船舶加油策略，航线和速度的影响；并从示例分析中得出了见解。