Research team
Airline crew scheduling with multi-agent reinforcement learning
Abstract
The goal of this project is to accelerate and make the personnel planning process in the aviation sector more cost-efficient by, on the one hand, improving existing planning algorithms with ML methods, and on the other hand, developing a fully autonomous RL-driven planning solution using Reinforcement Learning (RL) and Multi-Agent Reinforcement Learning (MARL), leveraging the latest advancements in neural architectures.Researcher(s)
- Promoter: Mets Kevin
- Co-promoter: Verdonck Tim
- Fellow: van den Steen Yannick
Research team(s)
Project type(s)
- Research Project