Simulation mathematics and random number generation

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Simulation mathematics and random number generation: mathematics for simulation

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Winter Simulation Conference archive
Proceedings of the 33nd conference on Winter simulation table of contents

Arlington, Virginia

TUTORIAL SESSION: Advanced tutorials table of contents

Pages: 83 - 94

Year of Publication: 2001

ISBN:0-7803-7309-X

Author

Shane G. Henderson

Cornell University, Ithaca, NY

Sponsors

INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
NIST : National Institute of Standards and Technology
ACM: Association for Computing Machinery
SCS : The Society for Computer Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association

Publisher

IEEE Computer Society Washington, DC, USA

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ABSTRACT

I survey several mathematical techniques and results that are useful in the context of stochastic simulation. The concepts are introduced through the study of a simple model of ambulance operation to ensure clarity, concreteness and cohesion.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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	2	Billingsley, P. 1986. Probability and Measure, 2nd ed. Wiley, New York.
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	8	Shane G. Henderson, Mathematics and hybrid modeling: mathematics for simulation, Proceedings of the 32nd conference on Winter simulation, December 10-13, 2000, Orlando, Florida
	9	Shane G. Henderson , Peter W. Glynn, Computing Densities for Markov Chains via Simulation, Mathematics of Operations Research, v.26 n.2, p.375-400, May 2001 [doi>10.1287/moor.26.2.375.10562]
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