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<p>Screening experiments are procedures designed to identify the most important factors in simulation models. Previously proposed one-stage procedures such as sequential bifurcation (SB) and controlled sequential bifurcation (CSB) require factor effects to be arranged according to estimated sign or magnitude prior to screening. FF-CSB is a two-stage screening procedure for simulation experiments proposed by Sanchez et al. (2005) which uses an efficient fractional factorial experiment to estimate factor effects automatically, removing the need for pre-estimation. Empirical results show that FF-CSB classifies factor effects as well as CSB in fewer runs when factors are only grouped by their sign (positive or negative). In theory, the procedure can achieve more efficient run times when factors are also sorted by estimated effect after the first stage. This analysis tests the efficiency and performance characteristics of a sorted FF-CSB procedure under a variety of conditions and finds that the procedure classifies factors as well as unsorted FF-CSB with significant improvement in run times. Additionally, various model- and user-determined scenarios are tested in an initial attempt to parameterize run times against parameters known or controlled by the modeler. Further experimentation is also suggested.
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Bosché , Kerry N.</div>
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