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Lecturer(s)
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Semeniuk Martin, doc. Ing. Ph.D.
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Holý Richard, Ing. Bc. Ph.D.
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Lachman Petr, Ing.
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Course content
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The course introduces students to methodology, methods and practical application of simulation based on the principles of discrete simulation. 1. Introduction to simulation, use of simulation methods 2. Fundamentals of systems theory for simulation 3. Simulation models, examples 4. Creation of simulation models, examples 5. Simulation software 6. Random number generators 7. Basics of simulation language, classes, objects 8. Basics of simulation language, lists, examples 9. Simulation model control, timeline 10. Simulation model control, processes 11. Principles of distributed simulation 12. Experiment control, optimization algorithms - I. 13. Experiment control, optimization algorithms - II.
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Learning activities and teaching methods
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Lecture supplemented with a discussion, Lecture with practical applications, Project-based instruction, Multimedia supported teaching, Students' portfolio, Individual study
- Graduate study programme term essay (40-50)
- 40 hours per semester
- Contact hours
- 65 hours per semester
- Team project (50/number of students)
- 25 hours per semester
- Presentation preparation (report) (1-10)
- 5 hours per semester
- Preparation for an examination (30-60)
- 40 hours per semester
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| prerequisite |
|---|
| Knowledge |
|---|
| describe the system behavior by an algorithm |
| understand simple code written in at least one programming language |
| work independently and be able to further self-study |
| Skills |
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| use the theoretical knowledge of industrial engineering independently |
| based on the obtain knowledge to propose possible solutions of the problem |
| Competences |
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| N/A |
| N/A |
| N/A |
| learning outcomes |
|---|
| Knowledge |
|---|
| explain principles of discrete and continuous simulation |
| explain principles of functioning of discrete simulation models |
| explain the steps of solving simulation projects |
| explain principles of optimization algorithms used in discrete simulation |
| Skills |
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| create a simple discrete simulation model |
| analyze the modeled system for simulation purposes |
| verify the proposed solutions resulting from the analysis by simulation |
| teaching methods |
|---|
| Knowledge |
|---|
| Lecture supplemented with a discussion |
| Multimedia supported teaching |
| Interactive lecture |
| E-learning |
| Skills |
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| Project-based instruction |
| Individual study |
| Students' portfolio |
| E-learning |
| assessment methods |
|---|
| Knowledge |
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| Combined exam |
| Skills |
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| Seminar work |
| Group presentation at a seminar |
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Recommended literature
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Altiok, Tayfur; Melamed, Benjamin. Simulation modeling and analysis with Arena. Burlington : Academic Press, 2007. ISBN 978-0-12-370523-5.
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Bangsow, Steffen. Tecnomatix Plant Simulation : modeling and programming by means of examples. Softcover reprint of the original 1st edition 2016. 2016. ISBN 978-3-319-36449-0.
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Byoung Kyu Choi, DongHun Kang. Modeling and Simulation of Discrete Event Systems. Wiley, 2013. ISBN 978-1118386996.
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Dlouhý, Martin. Simulace podnikových procesů. Vyd. 1. Brno : Computer Press, 2007. ISBN 978-80-251-1649-4.
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Chung, Christopher A. Simulation modeling handbook : a practical approach. Boca Raton : CRC Press, 2004. ISBN 0-8493-1241-8.
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Raška, Pavel; Ulrych, Zdeněk. Simulační optimalizace. [Plzeň] : SmartMotion, 2013. ISBN 978-80-87539-38-5.
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Ulrych, Zdeněk; Raška, Pavel. Modelování a simulace a DP. [Plzeň] : SmartMotion, 2012. ISBN 978-80-87539-15-6.
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Ulrych, Zdeněk. Simulace výrobních systémů a procesů - Plant Simulation. [Plzeň] : SmartMotion, 2013. ISBN 978-80-87539-39-2.
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