When the simulation department of Management Science was created in 1978 it ushered in an era of significant methodological advances in stochastic simulation. However, the foundation for the field---not just the work that has been published in Management Science---was provided by two papers...

In the study of large, complex computer simulation models the user is often overwhelmed by the vast number of input variables. Moreover, he or she is usually confused about how to make an effective analysis of the model without performing an excessive number of runs, which tend to be costly and...

We present a general recipe for constructing experiment design and analysis procedures that simultaneously provide indifference-zone selection and multiple-comparison inference for choosing the best among k simulated systems. We then exhibit two such procedures that exploit the...

Data truncation is a commonly accepted method of dealing with initialization bias in discrete-event simulation. An algorithm for determining the appropriate initial-data truncation point for univariate output is proposed. The technique entails averaging across independent replications and...

This paper presents a procedure for determining the number of simulation observations required to achieve a preassigned confidence interval for means estimated by simulation. This procedure, which is simple to implement and efficient to use, is compared with two other methods for determining the...

We consider the problem of comparing a finite number of stochastic systems with respect to a single system (designated as the "standard") via simulation experiments. The comparison is based on expected performance, and the goal is to determine if any system has larger expected performance than...

We propose some new two-stage stopping procedures to construct absolute-width and relative-width confidence intervals for a simulation estimator of the steady-state mean of a stochastic process. The procedures are based on the method of standardized time series proposed by Schruben and on...

To optimize large-scale queuing systems configurations, OR professionals typically use discrete event simulation packages to examine in detail the movement of entities through such systems, assuming stochastic but fixed arrival patterns. Demand aspects are, however, routinely ignored as few...

This paper presents a new method, called the batch quantile method, for estimating quantiles in regenerative simulations. The quantile estimator is consistent and asymptotically normal, and the method can be easily implemented and does not require prior knowledge of the range of values the data...