Estimating Waiting Times from Transactional Data
INFORMS Journal on Computing · 1997 · Volume 9 · Issue 2
Abstract
Given transactional data consisting of service starting and finishing times in a queuing system with a Poisson arrival process and service in order of arrival, the distributions and moments of waiting times W 1 , …, W N , of customers within a busy period of length N are computed efficiently by exploiting an embedded Markov chain. All first moments E( W k ∣ data from busy period of length N ) are computed in O ( N 3 ) multiplications; finding the distributions of all W k on a set of n prespecified times requires O ( nN 3 ) multiplications; finding all r th order moments needs O ( rN 4 ) multiplications. The algorithms described are all new, as fast or faster than all known algorithms, and address a broader range of performance measures than the extant literature.
Keywords
queuing theory, analysis of transactional data
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