Abstract: The research object is the electrically-propelled ship “Offshore Oil 301”. The power source, 9L34DF dual-fuel diesel engine and the main-engine-propeller system is modeled. The wind resistance and additive wave resistance during the voyage is estimated according to the data from European Centre for Medium Range Weather Forecasts (with surface interpolation). The route of the voyage is divided in segments according to the navigation situations. A landscape adaptive particle swarm optimizer is introduced to achieve minimum EEOI under the constraints of time schedule, generator capacity and Climbing capability. The LAPSO algorithm is used to optimize sole power control and power-speed combined control respectively. The results are compared to the actual voyage data, which shows that sole power control optimization saves fuel gas 0.6 t and reduces EEOI by 0.38% while the combined control achieves 8.23 t of fuel saving and 5.25% of EEOI reduction.