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Ship voyage optimization systems are widely used in today's ocean-crossing ships to consider a ship's sailing safety and energy efficiency. Large uncertainties from the inputs of today's voyage optimization algorithms can reduce the reliability of voyage optimization systems, especially for more complex algorithms that involve more control variables in the optimization. This study first proposes a speed optimization algorithm, which considers the voluntary speed reduction for a ship voyage with fixed trajectories. Then, the capability of the proposed speed optimization method is investigated by comparing with conventional voyage planning methods that optimize a ship's sailing courses/trajectories. In particular, the effectiveness of handling uncertain inputs during the optimization process, such as ship speed-power performance models, metocean forecasts, is investigated for the two types of voyage optimization methods. Finally, the benefits of potential fuel saving are studied by incorporating this proposed algorithm for a ship's slow steaming strategies.

Ocean crossing ship structures are continuously suffering from wave loads when sailing at sea. The wave loads cause large variation of structural stresses, leading to fatigue accumulation in ship structures. For the fatigue life prediction of ship structures, it is important to obtain both the long-term distribution and the time history of wave-induced loads. An essential step is to get reliable wave statistics and accurate description of the stochastic nature of sea state along a ship's sailing routes during her service time. Generally, the wave statistics are provided by the classification societies as a joint probability of significant wave height and mean wave period, also known as wave scatter diagram. In addition, different statistical wave models have been developed to describe wave environments along arbitrary shipping routes based on different data sources, e.g., hindcast data, satellite measurements, buoys, etc. In this paper, two statistical wave models based on hindcast data and satellite wave measurements are briefly introduced and compared with the wave measurements carried out by onboard radar. Both of the wave models are then used to generate the wave environments along given shipping routes. The effectiveness of the wave models is demonstrated by comparing the stochastic nature and the statistical characteristics of simulated sea state histories with those of the source oceanographic data. Finally, an application of the wave model to the fatigue assessment is presented.

In this paper, a Three-Dimensional Dijkstra’s optimization algorithm is proposed to allow a ship to plan her waypoints and sailing speeds along each waypoint. It is expected to generate global optimum solutions for ship routes. Its capability of fuel saving as objectives is demonstrated by comparing its results with those obtained from other conventional voyage optimization algorithms, and the actual fuel consumption of a container ship with full-scale measurements. The proposed Three-Dimensional Dijkstra’s algorithm can generate global opti- mum ship routing encountering less harsh sea environment, leading to at least 5% reduction of fuel consumption within the analysed cases. Furthermore, it can perform multi-objective voyage optimization, such as minimum fuel, minimum damage accumulation, lowest crack propagation, etc., with accurate ETA in the planning process.