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Modelling, Simulation and Optimisation
This module deals with selected methods out of the research and application area of Computational Intelligence. Methods treated in the lectures and seminar projects are, for instance, evolutionary search and optimisation technologies, neural networks, sophisticated data mining technologies, artificial intelligence, and every kind of hybrid intelligent system.
Besides the basic foundations and a broader theory, these methods are applied to business issues or other application areas of interest for modelling, simulating and analysing problems, for evaluating and assessing data, as well as for obtaining viable alternatives and optimised solutions.
The potential impact of computational intelligence is investigated. Different cases are examined where computational intelligence can provide a substantial support, for instance in management science,operations research, logistics, finance and banking, and computer science.
On successful completion of this module, the students will have gained knowledge of the objectives, implementation and use of such methods of computational intelligence.
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ECTS |
6 |
Should be elected: | FT: 3rd PT: 3rd or 5th |
| Academic Module Coordinator | Prof. Dr. Rolf Dornberger | ||
| Lecturers | Prof. Dr. Thomas Hanne | ||
| Pre-requisites |
Stuctural Sciences: Quantitative Methods for Business (foundations in mathematics, statistics, and optimization), basic knowledge in programming (preferably Java) |
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| Overall hours | Contact hours: 60 h Self-Study: 120 h |
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| Outline Content |
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| Teaching and Learning Methods | This module is taught in plenary lectures and plenary/group workshops, including presentations and practical training with software tools. Class participation is actively encouraged. Plenary sessions will be accompanied by assignments to be done as homework. In the plenary lectures, students may be required to orally present results of guided self study or repetition of previous lectures. |
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