ACM Home Page
Please provide us with feedback. Feedback
ExpertFit: total support for simulation input modeling
Full text PdfPdf (506 KB)
Source Winter Simulation Conference archive
Proceedings of the 27th conference on Winter simulation table of contents
Arlington, Virginia, United States
Pages: 395 - 400  
Year of Publication: 1995
ISBN:0-7803-3018-8
Authors
Stephen Vincent  Averill M. Law & Associates, P.O. Box 40996, Tucson, Arizona
Averill M. Law  Averill M. Law & Associates, P.O. Box 40996, Tucson, Arizona
Sponsors
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation
ASA : American Statistical Association
NIST : National Institue of Standards & Technology
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
INFORMS/CS : Computer Science TC
SIGSIM: ACM Special Interest Group on Simulation and Modeling
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 7,   Citation Count: 3
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/224401.224643
What is a DOI?

ABSTRACT

We explain the important role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of ExpertFit, the Windows based successor to the UniFit II input modeling package. We use a set of real world system data to demonstrate how the package automatically specifies, evaluates, and ranks candidate probability distributions, and then assists an analyst in deciding whether the "best" candidate probability distribution provides an adequate representation of the data. If no candidate probability distribution provides an adequate fit, then ExpertFit can define an empirical distribution function. In either case, the probability distribution can be automatically expressed in the analyst's simulation software. We then consider the general case of selecting a probability distribution in the absence of data. As an example, we show how ExpertFit can be used to create busy time and downtime models for machines that are subject to random breakdowns.


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
 
2
 
3
Law, A.M., M.G. McComas, and S.G. Vincent. 1994. The Crucial Role of Input Modeling in Successful Simulation Studies. Industrial Engineering 26:55-59 (July 1994).


Collaborative Colleagues:
Stephen Vincent: colleagues
Averill M. Law: colleagues