Prof. Dr.-Ing. O. Stursberg
M.Sc. Nils Hanke

The objective of this course is to teach fundamental principles of mathematical optimization for engineering design. It will be explained how to determine optimal choices for degrees of freedom such that a selected performance or cost functional is optimized. The course covers techniques of continuous (unconstrained and constrained) optimization, as well as of discrete optimization. In addition to convey knowledge on principles and properties of these techniques, the course aims at providing insight into applying the methods to examples taken from different domains of application.

• Introduction into mathematic optimization
• Unconstrained optimization (line search methods, trust region methods, conjugate gradients, derivative-free methods, etc.)
• Principles of constrained optimization
• Linear programming
• Quadratic programming
• Nonlinear programming
• Discrete optimization (graph-based methods)
• Mixed-integer programming
• Application examples

• Lecture slides
• J. Nocedal, S.J. Wright: Numerical Optimization. Springer, 2nd ed., 2006.
• R. Fletcher: Practical Optimization. Wiley, 2nd ed., 1987.
• G. Nemhauser: Integer and Combinatorial Optimization. Wiley, 1999.

Fundamental knowledge of mathematics (algebra and analysis) as typically taught in Bachelor degree programs of Electrical Engineering.

3 L + 1 T,  6 Credit Points

(L: lecture hours per week, T: tutorial hours per week)

The course is offered in the winter semester; the examination in the winter and summer semester (in English only).

Note that the submission of a homework solution is mandatory for admittance to the exam.

FB16 - 4002

Master of Electrical Engineering

Master of Mechatronics

Master of Computer Science

(open as elective course within other programs)