Modeling and Simulation - Summer 17

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Summer 17
Univ.-Prof. Dr. Hans-Joachim Bungartz
Time and Place
Tuesdays, 16:45 - 18:15, Interim 1
Wednesdays, 16:15 - 17:45, MI HS 1
Modul IN2010
Informatics Diplom: Elective course in the field of theoretical computer science
Informatics Bachelor: Elective course
Information Systems(Wirtschaftsinformatik) Bachelor: Elective course
Informatics Master: Elective course in the Area of "Algorithms and Scientific Computing"
Computational Science and Engineering: Elective course (Application Catalogue E1)
Students of Mathematics, Science and Engineering
Paul Sarbu, Steffen Seckler
Mondays, 16:00 - 18:00, PH HS3 (second tutorial: 08.05.2017)
Tuesdays, 8:15 - 9:45, MI 02.07.023 (second tutorial: 09.05.2017)
1st exam: 11.08.2017 at 8:00 am in MW 0001
Exam Review on 28.08.2017 between 10:00 hrs and 12:00 hrs in MI 02.07.023
2nd exam: 12.10.2017 at 15:30 in MI HS 1
Exam Review for 2nd exam on 02.11.2017 between 15:00 hrs and 16:30 hrs in MI 00.08.053
Semesterwochenstunden / ECTS Credits
6 SWS (4V + 2Ü) / 8 Credits
Lecture, Tutorial, Moodle

Current Issues

Exam Instructions

  • You may only use one hand-written sheet of paper (size A4, on both pages).
  • Any other material including electronic devices of any kind is forbidden.
  • Do not use pencil, or red or green ink.


Models are simplifying abstract representations of real systems, simulations are (mostly/always) computer-aided experiments, based upon a model. To understand, predict and optimize the behavior of a system more efficient and expressive simulations are necessary. Corresponding to the immense variety of modelling, as well as to-be-modeled systems (e.g. climate, weather, chemical or biological reactions, crash-tests, stock prices, scheduling, traffic, traffic in computing systems, software systems) a wide range of fundamentally different mathematical and informatical methods is used. Those can be deterministic or stochastic, discrete or numeric, but also less formal methods, as textual or graphic descriptions (e.g diagrams). Nevertheless there exist various general principles, e.g. for the derivation, analysis or evaluation of a model.

In this lecture an introduction to mathematical-informatical modeling is given. Hereby various topics are discussed. This includes model classes, the choice of proper instruments to formally describe a model, the derivation of models, as well as properties of models.

Multiple examples of discrete models and simulation methods (Decision theory, scheduling, discrete event simulation), as well as examples of continuous models and their simulation techniques (population dynamics, control theory, traffic simulations, heat conduction) from a wide range of scientific backgrounds are presented. Hereby the necessary tools, the derivation of the model, and its realization in a simulation are elaborated.

This lecture shines light on these topics in the context of computer science. The necessary mathematical contents are discussed; this course does not require the students to have any prior knowledge that exceed the undergraduate level.


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