This course provides a comprehensive overview of optimization techniques such as linear and integer programming, and non-linear programming, with applications in game theory and economics. Students learn optimization techniques from mathematics and operations research, and how to apply them in models from game theory and economic theory.

Game Theory and Optimization techniques are fundamental skills for Econometricians and Operations Researchers. This course provides an overview of the relevant tools in both subjects. The optimization part of this course focuses on (discrete) optimization problems and techniques. Topics covered include (integer) linear programming, and graph problems and flow algorithms. The game theory part covers the definition and computation of Nash equilibria, potential games and mechanism/auction design.

There are lecture notes available via Canvas.

Exchange students need to have obtained a BSc degree in Economics, International Business, Econometrics, or a related topic. Familiarity with the basic concepts of optimization and linear programming will be helpful. A solid basis in mathematics and calculus is also recommendable.