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Module guide WS 2018-2022

Module MA4031-KP08

Optimization (Advanced Mathematics) (OptiKP08)

Duration:


1 Semester
Turnus of offer:


each summer semester
Credit points:


8
Course of studies, specific field and terms:
  • Master CLS 2023 (compulsory), 1st, 2nd, or 3rd semester
  • Master CLS 2016 (compulsory), 1st, 2nd, or 3rd semester
Classes and lectures:
  • Optimization (exercise, 2 SWS)
  • Optimization (lecture, 4 SWS)
Workload:
  • 130 Hours private studies and exercises
  • 90 Hours in-classroom work
  • 20 Hours exam preparation
Contents of teaching:
  • Linear optimization (simplex method)
  • Unconstrained nonlinear optimization (gradient descent, conjugate gradients, Newton method, Quasi- Newton methods, globalization)
  • Equality- and inquality-constrained nonlinear optimization (Lagrange multipliers, active set methods)
  • Stochastic methods for machine learning
Qualification-goals/Competencies:
  • Students can model real-life problems as optimization problems.
  • They understand central optimization techniques.
  • They can explain central optimization techniques.
  • They can compare and assess central optimization techniques.
  • They can implement central optimization techniques.
  • They can assess numerical results.
  • They can select suitable optimization techniques for practical problems.
  • Interdisciplinary qualifications:
  • Students can transfer theoretical concepts into practical solutions.
  • They are experienced in implementation.
  • They can think abstractly about practical problems.
Grading through:
  • Written or oral exam as announced by the examiner
Is requisite for:
Requires:
Responsible for this module:
Teachers:
Literature:
  • J. Nocedal, S. Wright: Numerical Optimization - Springer
  • F. Jarre: Optimierung - Springer
  • C. Geiger: Theorie und Numerik restringierter Optimierungsaufgaben - Springer
Language:
  • offered only in German
Notes:

Prerequisites for attending the module:
- None (Familiarity with the topics of the required modules is assumed, but the modules are not a formal prerequisite for attending the course).

Prerequisites for the exam:
- Exercises and their presentation are ungraded preliminary examinations. These must have been completed and positively evaluated before the first examination.

Examination:
- MA4031-L1: Optimization, written examination (90 min) or oral examination (30 min) as decided by examiner, 100% of final mark

Variant of MA4030, MA4030-KP08 for students who did not attend a course on optimization in their Bachelor’s program.

Letzte Änderung:
4.2.2022