Contents:
After concentrating on linear programming, integer linear programming, and some efficiently solvable discrete optimization problems in Optimierung und OR 1, we will focus in Optimierung und OR 2 on algorithmically hard problems, complexity theory, approximation algorithms, and heuristics. Furthermore, we will extend some of the fundamental results of linear programming to more general, and, in particular, convex optimization problems.

References:

• B. Korte and J. Vygen, Combinatorial Optimization: Theory and Algorithms, Springer
• V.V. Vazirani, Approximation Algorithms, Springer

Professor and Teaching Assistant: Dieter Rautenbach, Maximilian Fürst
Times: Lecture: tba
            Exercise: tba
Place: tba
Prerequisites for the exam ("Vorleistung"): 50% of the reachable points in the exercises as well as active participation during the exercise hours.
Exam: tba
Exercise sheets and further material: moodle.uni-ulm.de/login/index.php