Robust decision making for future train maintenance: Illustrating the abilities of decision making under deep uncertainty within the train maintenance context

This research has illustrated the abilities of incorporating robust decision making within train maintenance. Both scheduled and unscheduled maintenance processes of the Nederlandse Spoorwegen (NS) have been examined, after which exploratory modeling and analysis enabled developing valuable insights for decision makers. Scenario analysis through...

Exploring Trade-offs in Reservoir Operations through Many Objective Optimisation: Case of Nile River Basin

Water storage and diversion capacity of reservoirs in the Nile Basin are benefited for various purposes including agricultural irrigation and hydro-energy production. Filling and operation of the recently constructed Grand Ethiopian Renaissance Dam (GERD) have been subject to heated debate for its implications on downstream countries Sudan and...

REAL Reinforcement Learning: Planning with adversarial models

Model-Based Reinforcement Learning (MBRL) algorithms solve sequential decision-making problems, usually formalised as Markov Decision Processes, using a model of the environment dynamics to compute the optimal policy. When dealing with complex environments, the environment dynamics are frequently approximated with function approximators (such as...

Viability of the Dutch Inland Waterway Transport Sector: In The Context Of The Future Navigability Of The Rhine

At the UN conference of 2015, the promotion of inland waterway transport (IWT) was named as a Sustainable Development Goal by the United Nations. While IWT has been identified to make goods transport more CO2- efficient, the long-term viability of the Dutch IWT sector is at risk.<br/><br/>Currently, Dutch IWT businesses benefit from increased...

Modelling Uncertainty: Developing and Using Simulation Models for Exploring the Consequences of Deep Uncertainty in Complex Problems

Simulation models are increasingly used for exploring the consequences of deep uncertainty in complex societal issues. The complexity of societal grand challenges, often characterised by the interrelatedness of different elements in the systems underlying these challenges, often renders mental simulation impossible, necessitating the use of...