Modeling and Simulation - Summer 18

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Summer 18
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, Severin Reiz
Mondays, 16:15 - 17:45, PH HS3 (first tutorial: 16.04.2017)
Tuesdays, 8:15 - 9:45, Room change due to size issues MI 01.10.011 (first tutorial: 17.04.2017)
1st exam: Friday, 13th July 16:00-18:00
  • [A-R] (in MI HS1) and [S-Z] (in PH HS 2)
Semesterwochenstunden / ECTS Credits
6 SWS (4V + 2Ü) / 8 Credits
Lecture, Tutorial, Moodle

Current Issues

  • Consultation hours (Sprechstunden) - individual or in small groups only!!!
   ** Tue., June 19, 15:00 - 16:00, room MI 02.05.051 Due to upcoming important research meeting we had to reschedule. We apologize for inconvenience caused.
   ** Tue., June 26, 15:00 - 16:00, room MI 02.05.051
   ** Tue., July 03, 15:00 - 16:00, room MI 02.05.051
  • Exam: moved to 13.07. (Friday, the 13th..) due to >90% majority vote
  • Tuesday tutorial: Room change to MI 01.10.011. On 3.7. back in 02.07.023 (other room is booked)
  • We are recording the lectures from Apr 17th onwards and distribute through moodle. Nevertheless, we strongly encourage you to go to the lectures, participate, and use recordings only as a reference fall-back solution (e.g. for repetition and exam preparation)
  • Preliminary time schedule: 105 mins lectures to compensate for cancelled lectures
Tag Datum Zeit Misc
DI 10.04.18 16:45-18:30
MI 11.04.18 16:15-18:00
DI 17.04.18 16:45-18:30
MI 18.04.18 no lecture
DI 24.04.18 16:45-18:15 Substitute
MI 25.04.18 16:15-17:45 Substitute
DI 01.05.18 Holiday
MI 02.05.18 no lecture Tutorial will be held, since holiday on Tue
DI 08.05.18 Switch w/ TUT 7.5.2018, 16:30-18:00
MI 09.05.18 16:15-18:00
DI 15.05.18 16:45-18:30
MI 16.05.18 16:15-18:00
DI 22.05.18 Holiday
MI 23.05.18 16:15-18:00
DI 29.05.18 16:30-18:45
MI 30.05.18 no lecture
DI 05.06.18 16:45-18:15 Substitute
MI 06.06.18 16:15-17:45 Substitute
DI 12.06.18 16:45-18:30 Hanuta-Challenge, Evaluation
MI 13.06.18 16:15-18:00
DI 19.06.18 16:45-18:30
MI 20.06.18 16:15-18:00
DI 26.06.18 16:45-18:30
MI 27.06.18 16:15-18:00
DI 03.07.18 16:45-18:30
MI 04.07.18 16:15-18:00
DI 10.07.18 16:45-18:30
MI 11.07.18 16:15-18:00

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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