A weather routing tool is presented based on forecasted weather data along the route and considering safety aspects. The tool aims to determine the optimal path for the minimisation of the fuel oil consumption, ensuring a safe passage. It is developed in MATLAB and considers detailed ship characteristics. Specifically, ship's motions and fuel oil consumption of the main engine during a potential path are estimated. For the latter, a physics-based model for a specific vessel is developed where tools of different level of detail are utilised to calculate the various resistance components. A speed management strategy along the route is specified as well as safety criteria representing acceptable limits of ship's responses. When the set criteria and constraints have been set, a genetic algorithm is used to find the optimal route by means of ship's heading or by considering both heading and ship's power settings as variables to minimise the fuel oil consumption. The search space of the algorithm lies within a predefined envelop, but still the evolutionary optimisation approach used has no pre-assigned values to any possible candidate waypoint.

This paper presents a methodology to support the decision-making process during the planning of ship operations. The methodology is designed with the aim of identifying and providing the operator with the best Estimated Time of Departure (ETD)–Estimated Time of Arrival (ETA) window of opportunity to execute the journey/operation between two predefined locations. To achieve this purpose, the International Maritime Organization (IMO) stability criteria are exploited in the process to formulate an operational safety criterion based on fuzzy reasoning as a function of the METeorological and OCeanographic (METOC) and sailing conditions. This allows for the analysis of the set of Pareto routes computed by a weather routing systems relying on a multi-objective set-up. The proposed methodology is tested in an operational scenario in the Mediterranean Sea.

Solving the problem of ship weather routing has been always a goal of nautical navigation research and has been investigated by many scientists. The operation schedule of an oceangoing ship can be influenced by wave or wind disturbances, which complicate route planning. In this paper, we present a real-coded genetic algorithm to determine the minimum voyage route time for point-to-point problems in a dynamic environment. A fitness assignment method based on an individual's position in the sorted population is presented, which greatly simplifies the calculation of fitness value. A hybrid mutation operator is proposed to enhance the search for the optimal solution and maintain population diversity. Multi-population techniques and an elite retention strategy are employed to increase population diversity and accelerate convergence rates. The effectiveness of the algorithm is demonstrated by numerical simulation experiments.

The wave climate along the main transoceanic routes of the North Atlantic sub basin is determined using three different databases: two derived by numerical models in the HIPOCAS and ERA40 databases and one from Voluntary Observing Ships. For each route the distribution of the mean significant wave height along the path is computed as well as the specific scatter diagram. In addition an assessment of the relative wave heading probability is provided. The results highlight a bias in the visual observations especially in the summer and, more in general, for low sea states. The correction of this bias allows better understanding of rough weather avoidance by ships and to determine a storm avoidance correction.

The main routes of ships voluntarily completing meteorological observations across the North Atlantic are detected by the intensity of the geographical distribution of the voluntary ship observations. The routes are then analysed in order to assess the relative intensity of traffic, the seasonal changes and the trend over the years. This paper will provide a better understanding of the North Atlantic trades and the relationship among the different routes, allowing the identification of the busiest areas. A discussion over the impact of routing on the weather that a transoceanic ship can experience during its life is also provided.

The paper presents a weather routing algorithm utilising a multi-objective optimisation with constraints, namely the Multi-objective Evolutionary Weather Routing Algorithm (MEWRA). In the proposed approach weather route recommendations can be made simultaneously e.g. for passage time, fuel consumption and safety of passage by means of Pareto optimisation. The sets of criteria and constraints in the optimisation process are fully customisable. The algorithm handles static (time-independent) and dynamic (time-dependent) constraints e.g. forecasted high wind speed regions or customisable areas to be excluded from routing (e.g. due to piracy). The paper includes a description of MEWRA as well as examples of its usage for finding Pareto-optimal transoceanic ship routes.