The queue inference engine: deducing queue statistics from transactional data
Article Abstract:
A technique to determine the queuing behavior of Poisson arrival queuing systems from Poisson assumption and transactional data is presented. The method suggests that for each period of congestion in which lines may form, the important quantities gathered are: the time-dependent mean number in the queue; the probability distribution of the number in the queue as observed by a randomly arriving customer; and mean waiting time in the queue. Research indicates findings are exact for a homogenous Poisson arrival procedure, and they are approximately correct for a Poisson procedure which displays a slow time variance.
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1990
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Locating a mobile server queueing facility on a tree network
Article Abstract:
Earlier in 1985, the authors developed a finite step algorithm to obtain an optimal location in their examination of a queueing-oriented facility location problem on a general network. Utilizing the same model, this analysis focuses on a tree network, finding simplifying properties of the objective function over paths of the tree. Two separate algorithms are created to search for the stochastic queue median (SQM) on a tree. The end product is an efficient algorithm that limits the search to a single well-defined path.
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1985
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An N server cutoff priority queue where arriving customers request a random number of servers
Article Abstract:
An N-server, multi-priority, Poisson arrival, nonpreemptive queue is considered in a police service allocation environment. The number of servers demanded is distributed along a known priority dependent probability. Service times are independent of each other, and independent of priority, system state and server identity. Lower priority customers are automatically queued in order to save servers for high priority customers.
Publication Name: Management Science
Subject: Business, general
ISSN: 0025-1909
Year: 1989
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