A comparison of selective initialization bias elimination methods

Jennifer R. Linton, Catherine Mary Harmonosky

Research output: Contribution to journalConference article

7 Citations (Scopus)

Abstract

When simulating a non-terminating system, the issue of initialization bias must be addressed. Many approaches have been developed to remove initialization bias from the output data. This paper provides a comparison of 5 selected methods applied to two slightly different 2-machine flow shop models. The experiment tests for statistical differences between mean and variance of the data used by each method to calculate steady state performance measures. Additionally, for each method, the practicality and ease-of-use for general applicability in larger modeled environments is discussed.

Original languageEnglish (US)
Pages (from-to)1951-1957
Number of pages7
JournalWinter Simulation Conference Proceedings
Volume2
StatePublished - Dec 1 2002
EventProceedings of the 2002 Winter Simulation Conference - San Diego, CA, United States
Duration: Dec 8 2002Dec 11 2002

Fingerprint

Initialization
Elimination
Flow Shop
Experiments
Performance Measures
Calculate
Output
Experiment
Model

All Science Journal Classification (ASJC) codes

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

Cite this

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A comparison of selective initialization bias elimination methods. / Linton, Jennifer R.; Harmonosky, Catherine Mary.

In: Winter Simulation Conference Proceedings, Vol. 2, 01.12.2002, p. 1951-1957.

Research output: Contribution to journalConference article

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AB - When simulating a non-terminating system, the issue of initialization bias must be addressed. Many approaches have been developed to remove initialization bias from the output data. This paper provides a comparison of 5 selected methods applied to two slightly different 2-machine flow shop models. The experiment tests for statistical differences between mean and variance of the data used by each method to calculate steady state performance measures. Additionally, for each method, the practicality and ease-of-use for general applicability in larger modeled environments is discussed.

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