Optimization

The students know fundamental methods and algorithms for optimization problems. They are able to
model small real-world problems and to apply optimization techniques to solve those problems. The students broaden their analytical and problem-solving skills. They are able to acquire, adapt and apply current research results.

E.g.: Linear programs in standard form, fundamental theorem of linear optimization, Simplex-method,
duality theorem, degenerate problems, inner point methods, optimality conditions for unconstrained and
constrained problems, one-dimensional minimization; direct methods, descent methods in higher dimensions, cg-methods, basics of graph theory, optimization on graphs, methods of integer optimization.

Die Übung kann durch ein Seminar ersetzt werden und hat dann ein Gruppengröße von 15 Teilnehmern.

Studiensemester:                            1., 2.  oder 3. Semester

Modulbeauftragter:                         Ruzika

Lehrende:                                       Ruzika

Voraussetzungen (inhaltlich)           Extended Knowledge in linear algebra, analysis and numerics and
                                                        stochastics. Basis knowledge in mathematical modeling.

Turnus:                                           Sommersemester

Sprache:                                         Englisch

Standort:                                         Campus Koblenz