Robust modelling and optimisation in stochastic processes using impreciseprobabilities, with applications to queueing Ghent University
A process is called stochastic when its time-evolution is to some
extent uncertain. To model and reason with such uncertainty, we
use methods from probability theory. This allows us to analyse the
behaviour of these processes, and to design or influence them in
order to make their behaviour optimal or desirable.
One crucial problem is that most often we are not only uncertain
about the processes themselves, but ...