The goal is to address importat optimization problems as regards their mathematical formaulation and their efficient solution. In partiuclar concepts which are covered include constraint versus unconstraint optimization, convex optimization, duality, nonlinear optimization, discrete optimization and relaxation. A few important methods are covered including conjugate gradient, quasi Newton methods, interior point methods, Lagrange multipliers and barrier functions, and exemplary global optimization methods such as evolutionary strategies or local search.
Programmierkenntnisse (Python oder vergleichbar), Grundlagen Mathematik,
Frequency | Weekday | Time | Format / Place | Period |
---|
Module | Course | Requirements | |
---|---|---|---|
39-Inf-AOpt Applied Optimisation | Applied Optimisation | Graded examination
|
Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
The lecture will be accompanied by combined practical / theoretical exercises and a final exam.
A corresponding course offer for this course already exists in the e-learning system. Teaching staff can store materials relating to teaching courses there: