In this paper we address the problem of finding the simulated system with the best (maximum or minimum) expected performance when the number of systems is large and initial samples from each system have already been taken. This problem may be encountered when a heuristic search procedure-perhaps one originally designed for use in a deterministic environment-has been applied in a simulationoptimization context. Because of stochastic variation, the system with the best sample mean at the end of the search procedure may not coincide with the true best system encountered during the search. This paper develops statistical procedures that return the best system encountered by the search (or one near the best) with a prespecified probability. We approach this problem using combinations of statistical subset selection and indifference-zone ranking procedures. The subset-selection procedures, which use only the data already collected, screen out the obviously inferior systems, while the indifference-zone procedures, which require additional simulation effort, distinguish the best from the less obviously inferior systems.
An airplane's ability to absorb delay while airborne is limited and costly. Because of this, the air traffic management system anticipates and manages excessive demand for scarce shared resources, such as arrival runways or busy airspace, so that the delay necessary for buffering can be spread out over a larger distance, or taken on the ground before departure. It is difficult to model these important dynamics in a standard queueresource simulation framework, which does not account for limited delay absorption capacity. The modeling methodology presented here captures these dynamics by employing a large number of independent threads of execution to monitor and enforce a large number of relatively simple mathematical relationships. These relationships calculate feasible time windows for each portion of each flight. The model was implemented in the SLX simulation language. The speed and scalability of SLX are essential to the approach, which would otherwise be impractical.
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