Optimal maintenance scheduling and vessel routing in offshore wind farms: A tailored column generation approach

The globally installed capacity of offshore wind farms has witnessed significant growth to support carbon neutrality targets, which brings increased requirements on maintenance activities to ensure their safe and reliable operations. To conduct maintenance activities, there is a need to deploy a service vessel fleet to transport technicians and spare parts to multiple wind turbines in offshore wind farms, which has an important consequence on maintenance costs and power generation losses due to delayed maintenance. For developing cost-effective maintenance schedules, this paper investigates a novel maintenance routing and scheduling problem that integrates multiple key factors: available maintenance time windows due to weather conditions, multiple maintenance types, heterogeneous vessel fleets, and cross-vessel technician sharing. Each shared technician is dispatched to a wind turbine by a vessel and picked up by another. To handle this intricate problem, a mixed-integer linear programming model is formulated for the problem, which is then reformulated as a route-based set-partitioning model based on a time-space network. Then, a tailored column generation approach is proposed to address the problem. Numerical experiments on real-world cases are conducted to validate solution quality and computational efficiency of the proposed approach. Besides, the importance of technician sharing and vessel fleet composition on reducing maintenance costs is confirmed by cost-effectiveness analysis.