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Lecturer(s)
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Semeniuk Martin, doc. Ing. Ph.D.
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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 |
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| Knowledge |
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| describe the behavior of the system using an algorithm |
| understand simple programming code written in some programming language |
| work independently and be able to further self-study |
| Skills |
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| independently use theoretical knowledge in the field of industrial engineering |
| on the basis of the acquired knowledge to suggest possible solutions to the given problem |
| Competences |
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| N/A |
| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| explain the principles of discrete event and continuous simulation |
| explain the principles of how discrete event simulation models work |
| explain the individual steps associated with the solution of simulation projects |
| explain the principles of optimization algorithms used in discrete event simulation |
| Skills |
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| create a simple discrete event simulation model |
| analyze the modeled system for simulation purposes |
| verify the proposed solutions resulting from the analysis using discrete event simulation |
| Competences |
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| N/A |
| N/A |
| N/A |
| teaching methods |
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| Knowledge |
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| Lecture supplemented with a discussion |
| Multimedia supported teaching |
| Interactive lecture |
| E-learning |
| Skills |
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| Project-based instruction |
| Individual study |
| E-learning |
| Competences |
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| Lecture supplemented with a discussion |
| Project-based instruction |
| assessment methods |
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| Knowledge |
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| Written exam |
| Skills |
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| Seminar work |
| Project |
| Competences |
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| Written exam |
| Seminar work |
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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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Banks Jerry, Carson John S., Nelson Barry L., Nicol David M. Discrete-Event System Simulation: Pearson New International Edition. Pearson Education Limited, USA, 2013. ISBN 978-1-292-02437-0.
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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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Chung, Christopher A. Simulation modeling handbook : a practical approach. Boca Raton : CRC Press, 2004. ISBN 0-8493-1241-8.
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