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In many simulation studies a large amount of time and money is spent on model development, but little effort is made to analyze the simulation output data in a proper manner. Since most simulation models use random variables as input, the output data are themselves random and care must therefore be taken in drawing conclusions about the system under study.(More)
One of the most important but neglected aspects of a simulation study is the proper design and analysis of simulation experiments. In this tutorial we give a state-of-the-art presentation of what the practitioner really needs to know to be successful. We will discuss how to choose the simulation run length, the warm-up-period duration (if any), and the(More)
In this tutorial we present techniques for building valid and credible simulation models. Ideas to be discussed include the importance of a definitive problem formulation, discussions with subject-matter experts, interacting with the decision-maker on a regular basis, development of a written assumptions document, structured walk-through of the assumptions(More)
In this paper, we explain the important role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of ExpertFit, the Windows-based successor to the UniFit II input(More)
In this tutorial we present an introduction to simulation-based optimization, which is, perhaps, the "hottest" topic in discrete-event simulation today. We give a precise statement of the problem being addressed and also experimental results for two commercial optimization packages applied to a manufacturing example with seven decision variables.