The rapid growth expected in the offshore wind sector presents a growing opportunity to find savings from conducting operations and maintenance activities more efficiently. The predicted increase in the size and quantity of offshore wind farms means that mathematical tools for scheduling maintenance activities will be necessary to exploit economies of scale fully.

In order to complete an activity, a predetermined combination of skilled personnel, equipment and vessel support is required to be present at its location for the duration of the task. A fleet of heterogeneous fleet of vessels is responsible for both transporting the resources around the wind farm and conducting personnel transfers. Vessel movements must also account for limitations imposed by offshore weather conditions and the periodic need to return resources to port.

In this research, we have developed a mathematical model capable of determining the best routes for vessel movements and the ideal times to undertake crew transfers. Our mixed-integer programming formulation can compute high quality schedules that minimize the twin costs of performing maintenance and lost production. We extend our optimization model to include a set of scenarios that represent the stochastic evolution of weather and sea conditions in future shifts. Solving the resulting model with a rolling horizon approach allows us to produce a detailed solution for the current shift, which contains actions informed by future weather patterns.