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

Large Specialization Module Optimization
(dt. Großes Vertiefungsmodul Optimierung)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload
Lecture (4 SWS), recitation class (2 SWS),
270 hours (90 h attendance, 180 h private study)
Credit points,
formal requirements
9 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.
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.


Applicability

Module imported from M.Sc. Business Mathematics.

It can be attended at FB12 in study program(s)

  • B.Sc. Mathematics
  • B.Sc. Business Mathematics
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Informatics
  • M.Sc. Business Mathematics

When studying M.Sc. Data Science, this module can be attended in the study area Advanced and Specialization Modules in Mathematics.

The module is assigned to the focus area Scientific Computing. Further information on eligibility can be found in the description of the study area.


Recommended Reading

  • Depending on the course.



Please note:

This page describes a module according to the latest valid module guide in Summer semester 2021. 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.