Spreadsheet simulation

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Spreadsheet simulation: spreadsheet simulation

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Winter Simulation Conference archive
Proceedings of the 34th conference on Winter simulation: exploring new frontiers table of contents

San Diego, California

SESSION: Introductory tutorials table of contents

Pages: 17 - 22

Year of Publication: 2002

ISBN:0-7803-7615-3

Author

Andrew F. Seila

The University of Georgia, Athens, GA

Sponsors

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

Publisher

Winter Simulation Conference

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Downloads (6 Weeks): 0, Downloads (12 Months): 11, Citation Count: 0

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ABSTRACT

"Spreadsheet simulation" refers to the use of a spreadsheet as a platform for representing simulation models and performing the simulation experiment. This tutorial explains the reasons for using this platform for simulation, discusses why this is frequently an efficient way to build simulation models and execute them, describes how to setup a spreadsheet simulation, and finally examines when a spreadsheet is not an appropriate platform for simulation.

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.

	1	Alexopoulos, C., and A. F. Seila. 1998. Output data analysis. In Handbook of Simulation: Principles, Methodology, Advances, Applications, and Practice, ed. J. Banks. New York: John Wiley.
	2	Cheng, R. C. H. 1998. Random variate generation. In Handbook of Simulation: Principles, Methodology, Advances, Applications, and Practice, ed. J. Banks. New York: John Wiley.
	3	Fishman, G. S. 1996. Monte carlo concepts, algorithms and applications. New York: Springer.
	4	F. Fumero , C. Vercellis , Hai Yang , Thomas A. Grossman, Teachers' Forum: Spreadsheet Modeling and Simulation Improves Understanding of Queues, Interfaces, v.29 n.3, p.88-103, March 1999 [doi>10.1287/inte.29.3.88]
	5	Mattesich, R. 1961. Budgeting models and system simulation. The Accounting Review 36:384--397.

Collaborative Colleagues:

Andrew F. Seila: colleagues

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