Examples for typical OR problems.

Linear Programming: Basic notions, simplex method, duality, special versions of the simplex method (dual simplex method, three phase method), sensitivity analysis, parametric optimization, game theory.

Graphs and Networks: Basic notions of graph theory, shortest paths in networks, project scheduling, maximal and minimal cost flows in networks.

Learning objectives:

The student

• names and describes basic notions of linear programming as well as graphs and networks,
• knows the indispensable methods and models for quantitative analysis,
• models and classifies optimization problems and chooses the appropriate solution methods to solve optimization problems independently,
• validates, illustrates and interprets the obtained solutions.

• Nickel, Rebennack, Stein, Waldmann: Operations Research, 3. Auflage, Springer, 2022
• Hillier, Lieberman: Introduction to Operations Research, 8th edition. McGraw-Hill, 2005
• Murty: Operations Research. Prentice-Hall, 1995
• Neumann, Morlock: Operations Research, 2. Auflage. Hanser, 2006
• Winston: Operations Research - Applications and Algorithms, 4th edition. PWS-Kent, 2004