My PhD research focuses on the planning of offshore maintenance policies and is part of the project sustainable service logistics for offshore wind farms (university project page) funded by NWO. Effective maintenance planning, inventory control, and service logistics are crucial to significantly reduce the overall costs of offshore wind farms. However, the specific characteristics of the offshore wind supply chain imply several major research challenges. In my studies, I use operations research techniques to study maintenance, inventory, and logistics strategies that take into account the specific characteristics of offshore wind farms. Extensive numerical analyses provide insights that can be used in practice. The models developed are general maintenance models and are applicable for other maintenance problems as well.
My research is mainly based on the following techniques:
- Markov Decision Processes
- Valid inequalities - Branch-and-cut - Branch-and-bound
- Metaheuristics - ALNS - Genetic algorithms - Iterative Local Search
- Reinforcement Learning - DQN - A3C (work in progress)