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Modul
Mathematical Programming [M-WIWI-101473]
Credits
9Recurrence
Jedes SemesterDuration
1 SemesterLanguage
German/EnglishLevel
4Version
7Responsible
Organisation
- KIT-Fakultät für Wirtschaftswissenschaften
Part of
Bricks
Identifier | Name | LP |
---|---|---|
T-WIWI-102724 | Nonlinear Optimization I | 4.5 |
T-WIWI-102715 | Operations Research in Supply Chain Management | 4.5 |
T-WIWI-102725 | Nonlinear Optimization II | 4.5 |
T-WIWI-111247 | Mathematics for High Dimensional Statistics | 4.5 |
T-WIWI-102855 | Parametric Optimization | 4.5 |
T-WIWI-110162 | Optimization Models and Applications | 4.5 |
T-WIWI-102720 | Mixed Integer Programming II | 4.5 |
T-WIWI-102726 | Global Optimization I | 4.5 |
T-WIWI-102719 | Mixed Integer Programming I | 4.5 |
T-WIWI-103124 | Multivariate Statistical Methods | 4.5 |
T-WIWI-103638 | Global Optimization I and II | 9 |
T-WIWI-103637 | Nonlinear Optimization I and II | 9 |
T-WIWI-102727 | Global Optimization II | 4.5 |
T-WIWI-112109 | Topics in Stochastic Optimization | 4.5 |
T-WIWI-106548 | Advanced Stochastic Optimization | 4.5 |
T-WIWI-106549 | Large-scale Optimization | 4.5 |
T-WIWI-102856 | Convex Analysis | 4.5 |
T-WIWI-111587 | Multicriteria Optimization | 4.5 |
T-WIWI-102723 | Graph Theory and Advanced Location Models | 4.5 |
Competence Certificate
The assessment is carried out as partial exams (according to Section 4(2), 1 or 2 of the examination regulation) of the single courses of this module, whose sum of credits must meet the minimum requirement of credits of this module. The assessment procedures are described for each course of the module seperately.
The overall grade of the module is the average of the grades for each course weighted by the credits and truncated after the first decimal.
Competence Goal
The student
- names and describes basic notions for advanced optimization methods, in particular from continuous and mixed integer programming,
- knows the indispensable methods and models for quantitative analysis,
- models and classifies optimization problems and chooses the appropriate solution methods to solve also challenging optimization problems independently and, if necessary, with the aid of a computer,
- validates, illustrates and interprets the obtained solutions,
- identifies drawbacks of the solution methods and, if necessary, is able to makes suggestions to adapt them to practical problems.
Prerequisites
There is no compulsory course in the module.
Content
The modul focuses on theoretical foundations as well as solution algorithms for optimization problems with continuous and mixed integer decision variables.
Workload
The total workload for this module is approximately 270 hours.