Article

Free access

Eliminating event cancellation in discrete event simulation

Authors:

Eric L. Savage,

Lee W. SchrubenAuthors Info & Claims

WSC '95: Proceedings of the 27th conference on Winter simulation

Pages 744 - 750

https://doi.org/10.1145/224401.224722

Published: 01 December 1995 Publication History

PDF eReader

Abstract

The cancellation of previously scheduled events not only results in a model running less efficiently, it precludes the application of some analysis techniques such as infinitesimal perturbation analysis. While same simulation languages (SIMSCRIPT, SIGMA) include an explicit facility for event cancellation, others do not (SLAM, GPSS, SIMAN). From computation theory, it is known that event cancellation is never necessary; but it is sometimes a convenient modeling technique. Unfortunately, there has been no general methodology developed for eliminating event cancellation from a simulation model. We present a simple general approach. Applications to two classical models where event cancellation is typically used serve as illustrations of the method.

References

[1]

Cola, B. A. and R, G. Sargent. 1989. Automatic Lookahead Computation for Conservative Distributed Simulation, CASE Center Technical Report No. 8916, Syracuse University, Syracuse, NY.

Google Scholar

[2]

Glasserman, P. 1991. Structural Conditions for Perturbation Analysis Derivative Estimation: Finite Time Performance Indices. Operations Research 39:724-738

Digital Library

Google Scholar

[3]

Glynn, P. 1989. A GSMP Formalism for Discrete Event Systems. Proceedings of the IEEE 77 (1): 14-23.

Crossref

Google Scholar

[4]

Iglehart, D. L. and G. S. Shedler. 1983. Simulation of Non-Markovian Systems. IBM Journal of Research and Development 27(5):472-479.

Digital Library

Google Scholar

[5]

Narain, S. 1991. An Axiomatic Basis For General Discrete Event Modeling. Proceedings of the 1991 Winter Simulation Conference (B. L. Nelson, W. D. Kelton and G. M. Clark, eds.), Phoenix, AZ, 1073-1082.

Digital Library

Google Scholar

[6]

Schruben, L. W. 1993. Simulation Modeling with Event Graphs. Convnunications of the A CM 26(11):957-963.

Digital Library

Google Scholar

[7]

Som, T. K. and R. G. Sargent. 1989. A Formal Development of Event Graphs as an Aid to Structured and Efficient Simulation Programs. ORSA Journal on Computing 1(2):107-125.

Crossref

Google Scholar

[8]

Yucesan, E. 1989. Simulation Graphs for Design and Analysis of Discrete Event Simulation Models, Ph.D. Dissertation, School of OR&m, Comell University, Ithaca, NY.

Google Scholar

[9]

Yucesan, E. and L. W. Schruben. 1992. Structural and Behavioral Equivalence of Simulation Models. A CM Transactions on Modeling and Computer Simulation 2(1):82-103.

Digital Library

Google Scholar

Cited By

View all

(2013)ReferencesModeling and Simulation of Discrete‐Event Systems10.1002/9781118732793.refs(395-399)Online publication date: 9-Aug-2013
https://doi.org/10.1002/9781118732793.refs
Schruben L(2010)Simulation modeling for analysisACM Transactions on Modeling and Computer Simulation10.1145/1667072.166707420:1(1-22)Online publication date: 8-Feb-2010
https://dl.acm.org/doi/10.1145/1667072.1667074
Chan WSchruben LJefferson TFowler JIngalls R(2008)Mathematical programming representations for state-dependent queuesProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516839(495-501)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1516839
Show More Cited By

Index Terms

Eliminating event cancellation in discrete event simulation
1. Computing methodologies
  1. Modeling and simulation
2. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory

Recommendations

Discrete-event simulation and the event horizon

The event horizon is a very important concept that is useful for both parallel and sequential discrete-event simulations. By exploiting the event horizon, parallel simulations can process events in a manner that is risk-free (i.e., no antimessages) in ...
Inside discrete-event simulation software: how it works and why it matters
WSC '10: Proceedings of the Winter Simulation Conference

This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, control elements and operations; simulation runs; entity states; ...
Inside discrete-event simulation software: how it works and why it matters
WSC '13: Proceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World

This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, control elements and operations; simulation runs; entity states; ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

WSC '95: Proceedings of the 27th conference on Winter simulation

December 1995

1493 pages

ISBN:0780330188

Chairmen:
William R. Lilegdon
Pritsker Corp., West Lafayette, IN
,
David Goldsman
Georgia Institute of Technology, Atlanta
,
Editors:
Christos Alexopoulos
Georgia Institute of Technology, Atlanta
,
Keebom Kang
Naval Postgraduate School, Monterey, CA

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 December 1995

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Article

Conference

WSC95

Sponsor:

IIE
IEEE-SMCS
INFORMS/CS
ASA
ACM
SCS
SIGSIM
IEEE-CS
NIST

WSC95: 1995 Winter Simulation Conference

December 3 - 6, 1995

Virginia, Arlington, USA

Acceptance Rates

WSC '95 Paper Acceptance Rate 122 of 183 submissions, 67%;

Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
271
Total Downloads

Downloads (Last 12 months)78
Downloads (Last 6 weeks)8

Reflects downloads up to 20 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

(2013)ReferencesModeling and Simulation of Discrete‐Event Systems10.1002/9781118732793.refs(395-399)Online publication date: 9-Aug-2013
https://doi.org/10.1002/9781118732793.refs
Schruben L(2010)Simulation modeling for analysisACM Transactions on Modeling and Computer Simulation10.1145/1667072.166707420:1(1-22)Online publication date: 8-Feb-2010
https://dl.acm.org/doi/10.1145/1667072.1667074
Chan WSchruben LJefferson TFowler JIngalls R(2008)Mathematical programming representations for state-dependent queuesProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516839(495-501)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1516839
Ingalls RMorrice DWhinston A(1996)Eliminating canceling edges from the simulation graph model methodologyProceedings of the 28th conference on Winter simulation10.1145/256562.256821(825-832)Online publication date: 8-Nov-1996
https://dl.acm.org/doi/10.1145/256562.256821

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Discrete-event simulation and the event horizon

Inside discrete-event simulation software: how it works and why it matters

Inside discrete-event simulation software: how it works and why it matters