Input modeling tools for complex problems

Barry L Nelson*, Michael Yamnitsky

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncertain elements. Simple input models, consisting of independent and identically distributed sequences of random variates from standard probability distributions, are included in every commercial simulation language. Software to fit these distributions to data is also available. In this tutorial we describe input models that are useful when the input modeling problem is more complex.

Original languageEnglish (US)
Pages (from-to)105-112
Number of pages8
JournalWinter Simulation Conference Proceedings
Volume1
StatePublished - Dec 1 1998

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Software
  • Safety, Risk, Reliability and Quality
  • Applied Mathematics
  • Modeling and Simulation

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