MA5014 - Introduction to combinatorial optimization

Objectives

General objective:

At the end of this course, the student shall be able to take into account the different types of uncertainties on existing data in air transport optimisation problems, and this at any stage of the decision-making process (modelling, resolution and analysis).

Detailed objectives:

- Modelling uncertainties as conituous or discrete parameters (uncertainty scenario)
- Defining robustness criteria to assess solutions
- Modelling and assessing the cost of robustness
- Analysing and assessing the impact of an uncertainty on a problem
- Proposing deterministic or stochastic robust optimisation algorithms
- Analysing feedback in order to adjust a model and/or an optimisation under uncertainty method.