A comparison of five steady-state truncation heuristics for simulation
Proceedings of the 32nd conference on Winter simulation
Simulation: The Practice of Model Development and Use
Simulation: The Practice of Model Development and Use
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Starting a model from an unrealistic state can lead to initialization bias in the simulation output. This, in turn, can produce bias in the results and lead to incorrect conclusions. One method for dealing with this problem is to run the model for a warm-up period until steady state is reached and remove the initialization bias by deleting the data within that warm-up period. Our previous research identified the MSER-5 algorithm as the best candidate warm-up method for implementation into an automated output analysis system, and for inclusion into existing DES software products. However, during an attempt to implement an automatable sequential version of the MSER-5 procedure into existing discrete-event simulation software several issues arose. This paper describes the framework and associated adaption of MSER-5 in order to automate it. It then discusses in detail the implementation issues that arose and some potential solutions.