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This entry is from Summer semester 2021 and might be obsolete. No current equivalent could be found.
Nonlinear Optimization
(dt. Nichtlineare Optimierung)
Level, degree of commitment | Specialization module, depends on importing study program |
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. |
Origin | M.Sc. Business Mathematics, M.Sc. Business Mathematics |
Duration, frequency |
One semester, Regularly alternating with other courses in the research area of optimization |
Person in charge of the module's outline | Prof. Dr. Thomas Surowiec |
Contents
Fundamentals of nonlinear optimization: Kuhn-Tucker theory, minimization of nonlinear functions; minimization of nonlinear functions with constraints
Fundamentals of nonlinear optimization: Kuhn-Tucker theory, minimization of nonlinear functions; minimization of nonlinear functions with constraints
Qualification Goals
The students shall
- acquire a sound knowledge of the theory and practice of basic methods of optimization
- learn to recognize and assess the relevance of optimization methods for practical problems from different application areas such as parameter optimization, nonlinear regression, approximation, or optimal control,
- acquire the ability to model and solve optimization problems in practical situations,
- 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 Linear Algebra I and Analysis I and Analysis II or Basic Linear Algebra or Basic Real Analysis and Basics of Advanced Mathematics.
Applicability
The module 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 Mathematics
- LAaG Mathematics
When studying M.Sc. Business Mathematics, this module can be attended in the study area Specialization and Practical Modules in Mathematics.
The module can also be used in other study programs (export module).
The module is assigned to Applied Mathematics. Further information on eligibility can be found in the description of the study area.
Recommended Reading
- Alt, W.: Nichtlineare Optimierung, Vieweg, 2002
- Jarre, F., Stoer, J.: Nonlinear Programming, Springer, 2004
- Fletcher, R.: Practical Methods of Optimization, 2nd Edition, John Wiley & Sons, 1987
- Nocedal, J., Wright, S.: Numerical Optimization, Springer, 2002
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:
- Winter 2016/17
- Summer 2018
- Winter 2018/19
- Winter 2019/20
- Winter 2020/21
- Summer 2021
- Winter 2021/22
- Winter 2022/23
- Winter 2023/24 (no corresponding element)
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.