• Ries Bernard

• Ries Bernard

• Galby Esther

In this course, we start with a presentation of the basic notions in decision theory. We focus on several existing decision criteria and analyse their weaknesses and strengths. We particularly focus on decision criteria under probabilistic uncertainty and o how to handle additional information in a decision process. We then present an introduction to utility theory, explain how to use utility functions and also how to construct such functions using loteries.

In a second part, we will concentrate on network optimization problems (max flow, min cost flow, etc...). Our focus will be on the modeling part but we will also see how to solve such problems efficiently.

 Finally, we give a short introduction to multi-criteria decision theory and present some existing methods (ELECTRE, AHP).

All topics will be illustrated by examples taken from economics, management science and operations research.

1) Getting familiar with the basic vocabulary used in decision theory.

2) Understanding the differences between several decision criteria as well as their weaknesses and strengths.

3) Becoming familiar with uncertainty in decision making.

4) Being able to handle additional information in a decision process.

5) Understanding the basics in utility theory.

6) Being able to model and solve real world problems using network optimization techniques.

7) Getting familiar with multi-criteria decision problems and some existing methods.