ExpertFit total support for simulation input modeling

• Published in: Proceedings of the 27th conference on Winter simulation pp. 395 - 400
• Main Authors: Vincent, Stephen, Law, Averill M.
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 01.12.1995
• Series: ACM Conferences
• Subjects: Computing methodologies > Modeling and simulation > Model development and analysis; Computing methodologies > Modeling and simulation > Simulation support systems > Simulation languages; Computing methodologies > Modeling and simulation > Simulation theory; General and reference > Cross-computing tools and techniques > Design; Social and professional topics > Professional topics > Management of computing and information systems > Software management > Software maintenance; Software and its engineering > Software creation and management > Software post-development issues
• ISBN: 0780330188; 9780780330184
• DOI: 10.1145/224401.224643

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.