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A Terminal Bay Relief Strategy

Published online by Cambridge University Press:  27 July 2009

R. D. Doverspik
R. D. Doverspik
Affiliation:
Bell Communications Research 331 Newman Springs Road Red Bank, New Jersey 07701
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Abstract

This paper explores a new, more optimal policy for planning terminal bays for the provisioning of circuits in a telephone operating company. This new policy regularly monitors the terminal bay inventory and orders K units when the spare reaches a certain parameter, R. For particular office characteristics the optimal (R, K) pair which minimizes cost is determined, subject to a performance constraint. A probabilistic circuit demand model is formulated and a combination of simulation and analytic approximation is used to calculate the cost and performance measure. In order to prove that the new policy is more economical, the new policy is compared, via another simulation, to the present policy of a typical telephone operating company.

Type
Articles
Information
Probability in the Engineering and Informational Sciences , Volume 1 , Issue 4 , October 1987 , pp. 481 - 496
Copyright
Copyright © Cambridge University Press 1987

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References

Doverspike, R.D. (1984). A D-bay relief strategy. Bell Communications Research Technical Memorandum.Google Scholar
Smith, D.R. (1983). A model for special service circuit activity. Bell System Technical Journal 62 (10): 2911–2934.CrossRefGoogle Scholar
Zima, C.H. (1982). Preliminary analysis of Nucho's model of special services demand. AT&T Bell Labs Memorandum for File, File Case 39234.Google Scholar
Adelson, R.M. (1966). Compound Poisson distributions. Operations Research Quarterly, 17 (1): 73–75.CrossRefGoogle Scholar
Law, A.M. & Kelton, W.D. (1982). Simulation modeling and analysis. New York: McGraw-Hill.Google Scholar
Petitt, A.N. & Stephens, M.A. (1977). The Kolmogorov-Smirnov goodness-of-fit statistic with discrete and grouped data. Technometrics 19 (2): 205–210.CrossRefGoogle Scholar
Williams, D.A. (1984). A mathematical algorithm for the D-bay relief strategy. Bell Communications Research Technical Memorandum, TM–000–22331–84–O5.Google Scholar
Kitchin, J.F. & Hausman, R.E. (1982). A model of special service circuit connects and disconnects. Bell Labs Technical Memorandum, 82–54112–4.Google Scholar
Horn, P.S. (1983). Modeling the error distribution for special services forecasts. Bell Labs Technical Memorandum, 83–54113–3.Google Scholar