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 difficulties induced by autocorrelation of the output stream. But sample paths generated by stochastic simulation exhibit dynamic behaviour 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 when two systems have different utilisations and/or dynamic behaviour, and with simpler analysis resulting from the statistical independence of coefficient estimates at different frequencies.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Modeling and Simulation
- Management Science and Operations Research
- Information Systems and Management
- Industrial and Manufacturing Engineering