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Analysis of event-based, single-server nonstationary simulation responses using classical time-series models

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  • Brandão, Rita Marques
  • Porta Nova, Acácio M.O.

Abstract

In this article, we present a metamodeling methodology for analyzing event-based, single-server nonstationary simulation responses that is based on the use of classical ARIMA (or SARIMA) time-series models. Some analytical results are derived for a Markovian queue and are used to evaluate the proposed methodology. The use of the corresponding procedure is illustrated on a traffic example from the simulation literature. Some conclusions are drawn and recommendations for further work are stated.

Suggested Citation

  • Brandão, Rita Marques & Porta Nova, Acácio M.O., 2012. "Analysis of event-based, single-server nonstationary simulation responses using classical time-series models," European Journal of Operational Research, Elsevier, vol. 218(3), pages 676-686.
    • Handle: RePEc:eee:ejores:v:218:y:2012:i:3:p:676-686
    DOI: 10.1016/j.ejor.2011.11.039
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    References listed on IDEAS

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    1. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
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