Course content

Advanced Course in Complementarity Models and Equilibrium is an intensive PhD course given by Professor Steven A. Gabriel, University of Maryland and NTNU.

The course will cover topics in Nonlinear Programming and optimality conditions. Further it will give an overview of Mixed Complementarity Problems including the principle of symmetry and other optimization MCP Connections. We will describe the links to the variational inequality formulation and related theory about cones. We will define generalized Nash equilibriums. Finally the course will cover solution methods for MCPs/Vis/MPECs.

Learning outcome

After having completed the course the candidate should be able to

• define KKT conditions for non-linear programming models.
• formulate and solve Mixed Complementarity Problems.
• recognize and understand the links between MCP and optimization models and variational inequalities.
• choose between relevant solution methods to solve MCPs/Vis/MPECs.

Learning methods and activities

There will be in total 25 hours of lectures and a mandatory exercise.

Recommended previous knowledge

A previous course in MCPs/NLPs is desirable, as is at least a basic working knowledge of GAMS.

Course materials

Selected literature. Will be given at course start-up.