Shipping companies and maritime organizations want to improve the energy efficiency of ships and reduce fuel costs through optimization measures; however, the accurate fuel consumption prediction of fuel consumption is a prerequisite for conducting optimization measures. In this study, the white box models (WBMs), black box models (BBMs), and gray box models (GBMs) are developed based on sensor data. GBMs have great potential for the prediction of ship fuel consumption, but the lack of interpretability makes it difficult to determine the degree of influence of different influencing factors on ship fuel consumption, making it limited in practical engineering applications. To overcome this difficulty, this study obtains the importance of GBM input characteristics for ship fuel consumption by introducing the SHAP (SHAPley Additive exPlanations) framework. The experimental results show that the prediction performance of the WBM is much lower than that of the BBM and GBM, while the GBM has better prediction performance by applying the a priori knowledge of WBMs to BBMs. Combining with SHAP, a reliable importance analysis of the influencing factors is obtained, which provides a reference for the optimization of ship energy efficiency, and the best input features for fuel consumption prediction are obtained with the help of importance ranking results.

To comply with the regulations of emission control areas (ECAs), most operators have to switch to low-sulfur fuels inside the ECAs. Besides, a low-carbon objective is essential for long-term environmental protection; thus, is regarded as important as making profit. Therefore, the operators start making speed and route decisions under the two objectives of minimizing carbon emissions and maximizing profit. Drawing on existing methods, this paper formulates the profit and carbon emissions in sustainable coastal shipping, investigates the speed and route principles, and determines the best tradeoff between profit and carbon emissions. It is found that vessel speed should be set between emissions-optimum speed and profit-optimum speed, and the route must be selected in light of the speed decision. Next, the optimal choices of speed and route were examined under different scenarios and vessel types. The results show that the operation measures and objectives depend greatly on fuel price, vessel load, and vessel parameters. The operator should speed up the vessel if he/she wants to make more profit or if the scenario is favorable for profit making; e.g., low fuel price and high vessel load (LFHL). Large vessels should pursue more profit under LFHL conditions, without having to sail further outside the ECA. But this rule does not apply to small vessels. In addition, the operator should slow down the vessel inside the ECA and sail further, outside the ECA, with the growth in the price spread between marine gas oil (MGO) and heavy fuel oil (HFO), especially at a low HFO price. The research findings help operators to design operational measures that best suit the limit on sulfur content in fuel and the situation of the shipping market.