Using Partial Queue-Length Information to Improve the Queue Inference Engine's Performance
Name
OR-254-91.pdf
Size
2.3 MB
Format
Adobe PDF
Checksum (MD5)
9cc9de17965a165d7485807f6b05cb5c
Author(s)
Hall, Susan A.
Larson, Richard C., 1943-
Date Issued
May 1991
Publisher
Massachusetts Institute of Technology, Operations Research Center
Series/Report no.
Operations Research Center Working Paper;OR 254-91
Abstract
The Queue Inference Engine (QIE) uses queue departure time data over a single congestion period to infer queue statistics. With partial queue-length information, the queue statistics become more accurate and the computational burden is reduced. We first consider the case in which we are given that the queue length never exceeded a given length L. We then consider the more general case in which we are given the times of all L-to-(L + 1) and (L + 1)-to-L queue-length transitions. We present algorithms, parallel to the QIE algorithms,for deriving the queue statistics under the new conditioning information. We also present computational results, comparing both accuracy and computation time, under the QIE and the new algorithms, for several sample runs.
MIT Department
Massachusetts Institute of Technology. Operations Research Center
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