1. Mathematical modeling • Fundamental terms • Introduction of basic optimization problems • Modeling of important types of restrictions • Advanced modeling techniques 2. Linear Optimization • Fundamentals and definitions • Simplex-Algorithm • Advanced topics in linear optimization (e.g., duality and opportunity costs, upper and lower bounds) 3. Nonlinear Optimization • Unrestricted nonlinear problems • Advanced topics in nonlinear optimization (e.g., restricted nonlinear problems)

Learning outcomes

Upon successful completion of this module, students are able to • understand and formulate basic and advanced optimization problems. • evaluate basic and advanced optimization problems with respect to their complexity. • compare different optimization methods and choose appropriate optimization methods based on the given optimization problem. • apply appropriate optimization methods for different classes of optimization problems.
Number of credit hours per week 4