Transaction tagging in highly congested queueing simulations |
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Authors: | Lee W Schruben Enver Yucesan |
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Institution: | (1) School of Operations Research and Industrial Engineering Cornell University, 14853 Ithaca, NY, USA |
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Abstract: | The purpose of this paper is to illustrate how a very simple queueing model can be used to gain insight into a computer memory management strategy that is important for a large class of discrete-event simulation models. To this end, an elementary queueing model is used to demonstrate that it can be advantageous to run transaction-based simulations with a relatively few tagged transactions that collect data. The remaining transactions merely congest the system. Conceptually the tagged transactions flow through the simulation acting similar to radioactive trace elements inserted into a biological system. The queueing model analyzed in this paper provides insight into some trade-offs in simulation data collection. We show that, while resulting in a longer computer run, an optimal tagging interval greater than one will minimize the probability of prematurely aborting the run. Finally, we propose a heuristic procedure to estimate the optimal tagging interval. We illustrate this with an actual simulation study of a steel production facility.This research was partially supported by a grant to Cornell University by the Bethlehem Steel Corporation |
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Keywords: | Simulation data collection |
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