Fourier Trajectory Analysis For System Discrimination

Morgan, Lucy and Barton, Russell (2022) Fourier Trajectory Analysis For System Discrimination. European Journal of Operational Research, 296 (1). pp. 203-217. ISSN 0377-2217

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Abstract

With few exceptions, simulation output analysis has focused on static characterizations, to determine a property of the steady-state distribution of a performance metric such as a mean, a quantile, or the distribution itself. Analyses often seek to overcome diffculties induced by autocorrelation of the output stream. But sample paths generated by stochastic simulation exhibit dynamic behavior that is characteristic of system structure and associated distributions. In this paper, we explore these dynamic characteristics, as captured by the Fourier transform of a dynamic steady-state simulation trajectory. We find that Fourier coefficient magnitudes can have greater discriminatory power than the usual test statistics, and with simpler analysis resulting from the statistical independence of coefficient estimates at different frequencies.

Item Type:

Journal Article

Journal or Publication Title:

European Journal of Operational Research

Additional Information:

This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 296, 1, 2022 DOI: 10.1016/j.ejor.2021.05.052

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/2600/2611

Subjects:

?? simulationsystem discriminationfourier analysismodelling and simulationmanagement science and operations researchinformation systems and management ??

Departments:

Lancaster University Management School > Management Science

ID Code:

155754

Deposited By:

ep_importer_pure

Deposited On:

04 Jun 2021 09:20

Refereed?:

Yes

Published?:

Published

Last Modified:

31 Oct 2024 01:13

URI:

https://eprints.lancs.ac.uk/id/eprint/155754