Abstract
ABSTRACTThis article proposes a methodology, based on the use of a Taylor series expansion, for incorporating epistemic uncertainties in computing performance measures of retrial queueing models. Specifically, we investigate the M/M/1 retrial queue with finite size orbit, working vacation interruption, and classical retrial policy. The sensitivity analysis of the performance measures of the studied model is also provided. This analysis includes the estimation of the expected value and the variance of the performance measures associated with the studied queueing model. The efficiency of the proposed algorithm is assessed on several numerical examples.
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