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This entry is from Winter semester 2021/22 and might be obsolete. No current equivalent could be found.

Small Specialization Module Optimization
(dt. Kleines Vertiefungsmodul Optimierung)

Level, degree of commitment Specialization module, depends on importing study program
Forms of teaching and learning,
workload		 Lecture (3 SWS), recitation class (1 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises.
Examination type: Written or oral examination
Language,
Grading		 German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Business Mathematics.
Subject, Origin Mathematics, M.Sc. Business Mathematics, M.Sc. Business Mathematics
Duration,
frequency		 One semester,
irregular
Person in charge of the module's outline Prof. Dr. Thomas Surowiec

Contents

Unchecked automatic translation:
Depending on the event.

Possible topics are for example:

  • Optimization problems with differential equations (parameter estimation, optimal experimental design, process optimization)
  • Direct methods of optimal control in ODE and DAE (boundary value problem approach, structure-utilizing Gauss-Newton and SQP methods, local convergence sets of Newton-like methods, efficient globalization strategies, efficient generation of required derivatives)
  • Combinatorial optimization (minimal exciting trees and shortest path problems, flow problems, matchings, exact general solution methods, integer optimization)
  • Optimal control (Ordinary differential equations, stability theory, maximum principle, numerical methods, applications to economic and scientific processes)
  • Non-differentiable optimization

Depending on the event.

Possible topics are for example:

  • Optimization problems with differential equations (parameter estimation, optimal experimental design, process optimization)
  • Direct methods of optimal control in ODE and DAE (boundary value problem approach, structure-utilizing Gauss-Newton and SQP methods, local convergence sets of Newton-like methods, efficient globalization strategies, efficient generation of required derivatives)
  • Combinatorial optimization (minimal exciting trees and shortest path problems, flow problems, matchings, exact general solution methods, integer optimization)
  • Optimal control (Ordinary differential equations, stability theory, maximum principle, numerical methods, applications to economic and scientific processes)
  • Non-differentiable optimization

Qualification Goals

The students shall

  • be introduced to current research results from the field of optimization,
  • train working with research literature,
  • gain insight into the development of new mathematical results,
  • deepen their mathematical knowledge in the field of optimization,
  • acquire the competence to independently index current scientific contributions from national and international journals,
  • practice mathematical methods (development of mathematical intuition and its formal justification, training of the ability to abstract, proof methods),
  • improve their oral communication skills in the recitation classes by practicing free speech in front of an audience and during discussion.

Prerequisites

None. The competences taught in the following modules are recommended: either Foundations of Mathematics and Linear Algebra I and Linear Algebra II or Basic Linear Algebra, either Analysis I and Analysis II or Basic Real Analysis, Linear Optimization.


Recommended Reading

  • Depending on the course.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2021/22. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.