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- Title
DEDUCING QUEUEING FROM TRANSACTIONAL DATA: THE QUEUE INFERENCE ENGINE, REVISITED.
- Authors
Bertsimas, Dimitris J.; Servi, L. D.
- Abstract
R. Larson proposed a method to statistically infer the expected transient queue length during a busy period in O(n[sup 5]) solely from the n starting and stopping times of each customer's service during the busy period and assuming the arrival distribution is Poisson. We develop a new O(n[sup 3]) algorithm which uses these data to deduce transient queue lengths as well as the waiting times of each customer in the busy period. We also develop an O(n) on-line algorithm to dynamically update the current estimates for queue lengths after each departure. Moreover, we generalize our algorithms for the case of a time-varying Poisson process and also for the case of i.i.d. interarrival times with an arbitrary distribution. We report computational results that exhibit the speed and accuracy of our algorithms.
- Subjects
QUEUING theory; POISSON distribution; PRODUCTION scheduling; ALGORITHMS; STOCHASTIC processes; CUSTOMER services; OPERATIONS research
- Publication
Operations Research, 1992, Vol 40, Issue 3, p217
- ISSN
0030-364X
- Publication type
Article
- DOI
10.1287/opre.40.3.S217