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Unit 7: Simulation of Queuing System (I)
3. “Discrete-event technique has been widely used in the simulation of communication and Notes
transportation systems.” Comment.
4. Do you think Queuing Theory provides all the tools needed for this analysis?
5. Simulation is the experimental laboratory for testing modifications in a productive system
through the use of mathematical models. Give reasons.
6. Describe four specific models as valuable POM applications.
7. “The queuing system is the most typical problem in the discrete event system.” Explain.
8. Discuss the main conceptions in the Queuing System.
9. Simulating the model with event step-length method. Discuss.
10. Why queuing theory is a science to solve the problem?
Answers: Self Assessment
1. queuing system 2. static
3. single-channel 4. existing
5. timestamp 6. congestion
7. mathematical 8. Model Building
9. Evaluate 10. queuing problem
11. minitype 12. random
13. batch 14. waiting time
15. queuing regulation
7.8 Further Readings
Books Balci, O.,(1994), Validation, verification, and testing techniques throughout the
life cycle of a simulation study, Annals of Operations Research, 53: 121–173.
Balci, O., (2001), A methodology for certification of modelling and simulation
applications, ACM Transactions on Modelling and Computer Simulation, 11:
352–377.
Birta, L.G. and Ozmizrak, N.F., (1996), A knowledge-based approach for the
validation of simulation models: The foundation, ACM Transactions on Modelling
and Computer Simulation, 6: 67–98.
Boehm, B.W., (1979), Software engineering: R&D trends and defense needs, in: P.
Wegner (Ed.), Research Directions in Software Technology, MIT Press, and
Cambridge, MA.
Cellier, F.E., (1986), Combined discrete/continuous system simulation –
application, techniques and tools, in Proceedings of the 1986 Winter Simulation
Conference.
Department of Defense (DoD) Recommended Practices Guide (RPG) for Modelling
and Simulation VV&A, Millennium Edition (available at http://vva.dmso.mil).
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