Abstract: With the increasing proportion of refrigerated containers in container ships, the proportion of onboard daily power, including the cooling power of refrigerated containers, in the overall ship power is also rising. Consequently, this paper delves into the optimal sailing speed strategy for container ships in the face of the rising proportion of refrigerated containers. It establishes energy management optimization model tailored for long distance routes, optimizing container ship routes from the perspectives of cost and carbon emissions. Moreover, the model fully takes sea conditions' impact on ship speed into account and effectively resolves the complex logical coupling between long distance sea conditions and ship speed during optimization. Finally, a multi-objective genetic algorithm is applied to a Chinese coastal route, demonstrating that the proposed approach cuts total cost and CO₂ emissions by more than 5% relative to conventional practice, and yielding speed profiles that remain near-optimal across diverse environmental scenarios.

Key words: ship energy management, multi-objective optimization, uncertain parameters, multi-objective genetic algorithm, refrigerated containers