390053 DK PhD-L: Advanced Stochastic Models (2021W)
Continuous assessment of course work
Labels
MIXED
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 13.09.2021 09:00 to Th 23.09.2021 12:00
- Deregistration possible until Fr 15.10.2021 23:59
Details
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Monday 25.10. 12:55 - 16:00 Digital
- Monday 15.11. 13:00 - 16:00 Digital
- Monday 06.12. 13:00 - 16:00 Digital
- Monday 24.01. 13:00 - 16:00 Digital
- Monday 21.02. 09:45 - 16:30 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
- Tuesday 22.02. 09:45 - 16:25 Hörsaal 17 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
Presentations by the participants
Minimum requirements and assessment criteria
Examination topics
Participants need to be able to present their project in the context of models discussed, apply discussed modelling languages, propose relevant approaches to analysing stochastic input data and results, and present an implemented prototype.
Reading list
Recommended reading:- Robinson, S. (2005). Discrete-event simulation: from the pioneers to the present, what next?. Journal of the Operational Research Society, 56(6), 619-629.
- Tako, A. A., & Robinson, S. (2012). The application of discrete event simulation and system dynamics in the logistics and supply chain context. Decision Support Systems, 52(4), 802-815.
- Chan, W. K. V., Son, Y. J., & Macal, C. M. (2010, December). Agent-based simulation tutorial-simulation of emergent behavior and differences between agent-based simulation and discrete-event simulation. Proceedings of the 2010 Winter Simulation Conference (WSC), (pp. 135-150). IEEE.
- Sargent, Robert G. "Verification and validation of simulation models." Journal of Simulation 7, no. 1 (2013): 12-24.- Law: Simulation Modeling and Analysis (2014)
- Tako, A. A., & Robinson, S. (2012). The application of discrete event simulation and system dynamics in the logistics and supply chain context. Decision Support Systems, 52(4), 802-815.
- Chan, W. K. V., Son, Y. J., & Macal, C. M. (2010, December). Agent-based simulation tutorial-simulation of emergent behavior and differences between agent-based simulation and discrete-event simulation. Proceedings of the 2010 Winter Simulation Conference (WSC), (pp. 135-150). IEEE.
- Sargent, Robert G. "Verification and validation of simulation models." Journal of Simulation 7, no. 1 (2013): 12-24.- Law: Simulation Modeling and Analysis (2014)
Association in the course directory
Last modified: Fr 12.05.2023 00:26
- System dynamic, discrete event-based and agent-based simulation paradigms
- Analysis of stochastic simulation results
- The role of simulation validation and calibration
- Challenges of computational efficiency
They also gain hands-on experience in applying these concepts to case scenarios in implementing simulation models in Python SimPy and NetLogo.