In this study we have obtained stochastic equation systems of a Coxian queueing model with two phases where arrival stream of this model is according to the exponential distribution with λ parameter. The service time of any customer at server i (i=1,2) is exponential with parameter μ_i. In addition we have obtained state probabilities of this queueing model at any given t moment.Furthermore performance measures of this queueing system are calculated. Various queueing systems are found for some values of α probability and service parameters: if α=1and µ_1=µ_2taken then M/E_2/1/ 0 queueing model is obtained, for α=1it is shown that service time of a customer is according to hypoexponential, if α=0 is taken we have M/ M/1/ 0 queueing system. Lately,an application of this queueing model is done. The optimal value of the mean customer number in the system is found. Finally, optimal ordering according to the loss probability is obtained by changing the service parameters .A numerical example is given on the subject
Published in | Applied and Computational Mathematics (Volume 3, Issue 2) |
DOI | 10.11648/j.acm.20140302.11 |
Page(s) | 43-47 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2014. Published by Science Publishing Group |
Coxian Model, Differential Equations, Loss Probability, Limiting Distribution, Optimal Ordering
[1] | D.R. Cox, "A use of complex probabilities in the theory of stochastic processes. Proc. Camb. Phil. Soc.,"313-19, 1955. |
[2] | W. J. Stewart, "Probability, Markov Chains, Queues, Simulation, New Jersey,"2009. |
[3] | F.Neuts, "Probability distributions of phase type, in Liber Amicorum Professor Emeritus H.Florin, Department of Mathematics", University of Louvain, Louvain, Belgium 173-206. |
[4] | U. N. Bhat, "An Introduction to Queuing Theory," Boston, 2008. |
[5] | R.Marie, "Calculating Equilibrim Probabilities for (((λ(n))⁄C_k )⁄1)⁄N Queues," ACM Sigmetrics Performance Evaluation Review, Vol. 9, No.2, 1980. |
[6] | M. Zobu, V. Sağlam, M. Sağır, E. Yücesoy and T. Zaman"The Simulation and Minimization of Loss Probability in theTandem Queueing with Two Heterogeneous Channels," Mathematical Problems in Engineering, vol. 2013,Article ID 529010, 4, pages, 2013. |
[7] | M.Zobu "Using Sequential Analysis for Hypothesis Tests in The Phase-Type Distribution Queueing Systems," Ph.D. Thesis, OndokuzMayis University, Samsun, Turkey, 2013. |
[8] | D. Gross, C.M. Harris, "Fundamentals of Queuing Theory," Third Edition, John Wiley & Sons, New York, 1998. |
APA Style
Vedat Sağlam, Merve Uğurlu, Erdinç Yücesoy, Müjgan Zobu, Murat Sağır. (2014). On Optimization of a Coxian Queueing Model with Two Phases. Applied and Computational Mathematics, 3(2), 43-47. https://doi.org/10.11648/j.acm.20140302.11
ACS Style
Vedat Sağlam; Merve Uğurlu; Erdinç Yücesoy; Müjgan Zobu; Murat Sağır. On Optimization of a Coxian Queueing Model with Two Phases. Appl. Comput. Math. 2014, 3(2), 43-47. doi: 10.11648/j.acm.20140302.11
@article{10.11648/j.acm.20140302.11, author = {Vedat Sağlam and Merve Uğurlu and Erdinç Yücesoy and Müjgan Zobu and Murat Sağır}, title = {On Optimization of a Coxian Queueing Model with Two Phases}, journal = {Applied and Computational Mathematics}, volume = {3}, number = {2}, pages = {43-47}, doi = {10.11648/j.acm.20140302.11}, url = {https://doi.org/10.11648/j.acm.20140302.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20140302.11}, abstract = {In this study we have obtained stochastic equation systems of a Coxian queueing model with two phases where arrival stream of this model is according to the exponential distribution with λ parameter. The service time of any customer at server i (i=1,2) is exponential with parameter μ_i. In addition we have obtained state probabilities of this queueing model at any given t moment.Furthermore performance measures of this queueing system are calculated. Various queueing systems are found for some values of α probability and service parameters: if α=1and µ_1=µ_2taken then M/E_2/1/ 0 queueing model is obtained, for α=1it is shown that service time of a customer is according to hypoexponential, if α=0 is taken we have M/ M/1/ 0 queueing system. Lately,an application of this queueing model is done. The optimal value of the mean customer number in the system is found. Finally, optimal ordering according to the loss probability is obtained by changing the service parameters .A numerical example is given on the subject}, year = {2014} }
TY - JOUR T1 - On Optimization of a Coxian Queueing Model with Two Phases AU - Vedat Sağlam AU - Merve Uğurlu AU - Erdinç Yücesoy AU - Müjgan Zobu AU - Murat Sağır Y1 - 2014/03/20 PY - 2014 N1 - https://doi.org/10.11648/j.acm.20140302.11 DO - 10.11648/j.acm.20140302.11 T2 - Applied and Computational Mathematics JF - Applied and Computational Mathematics JO - Applied and Computational Mathematics SP - 43 EP - 47 PB - Science Publishing Group SN - 2328-5613 UR - https://doi.org/10.11648/j.acm.20140302.11 AB - In this study we have obtained stochastic equation systems of a Coxian queueing model with two phases where arrival stream of this model is according to the exponential distribution with λ parameter. The service time of any customer at server i (i=1,2) is exponential with parameter μ_i. In addition we have obtained state probabilities of this queueing model at any given t moment.Furthermore performance measures of this queueing system are calculated. Various queueing systems are found for some values of α probability and service parameters: if α=1and µ_1=µ_2taken then M/E_2/1/ 0 queueing model is obtained, for α=1it is shown that service time of a customer is according to hypoexponential, if α=0 is taken we have M/ M/1/ 0 queueing system. Lately,an application of this queueing model is done. The optimal value of the mean customer number in the system is found. Finally, optimal ordering according to the loss probability is obtained by changing the service parameters .A numerical example is given on the subject VL - 3 IS - 2 ER -