Computer-Aided Modeling and Optimization

Learning Objectives:

After attending this lecture, students will be able to model and solve practical optimization problems using commercial software packages (solvers). They are familiar with advanced modeling techniques and can apply them independently to given problems by implementing appropriate solution procedures in common modeling and optimization environments.

Contents:

• Optimization problems and methods
• Modeling of practical optimization problems
• Multicriteria optimization
• Algorithmic solution methods
• Branch and bound methods, cutting plane methods, column generation
• Commercial software packages (solvers, especially FICO Xpress)

Literature:

• Kallrath, J. (2002): Gemischt-ganzzahlige Optimierung: Modellierung in der Praxis
• Mellouli, T., Suhl, L. (2006): Optimierungssysteme
• T’kindt, V., Billaut, J.-C. (2006): Multicriteria Scheduling – Theory, Models and Algorithms, 2nd ed.
• Williams, P. H. (1999): Model Building in Mathematical Programming, 4th ed.