CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Analysis of FM/M(a,b)/1/MWV/Br Queueing Model

by K. Julia Rose Mary, R. Rajalakshmi, J. Pavithra
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 11
Year of Publication: 2016
Authors: K. Julia Rose Mary, R. Rajalakshmi, J. Pavithra
10.5120/ijca2016909799

K. Julia Rose Mary, R. Rajalakshmi, J. Pavithra . Analysis of FM/M(a,b)/1/MWV/Br Queueing Model. International Journal of Computer Applications. 142, 11 ( May 2016), 18-22. DOI=10.5120/ijca2016909799

@article{ 10.5120/ijca2016909799,
author = { K. Julia Rose Mary, R. Rajalakshmi, J. Pavithra },
title = { Analysis of FM/M(a,b)/1/MWV/Br Queueing Model },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 11 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 18-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number11/24939-2016909799/ },
doi = { 10.5120/ijca2016909799 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:44:42.342109+05:30
%A K. Julia Rose Mary
%A R. Rajalakshmi
%A J. Pavithra
%T Analysis of FM/M(a,b)/1/MWV/Br Queueing Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 11
%P 18-22
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we propose the general bulk service queueing model for FM/M(a,b)/1/MWV/Br. The batches are served according to FCFS discipline. In which arrival rate, vacation parameter, service rate for busy period, and for vacation period are all considered as trapezoidal fuzzy numbers. The basic idea is to convert all these fuzzy numbers into crisp values by applying Robust ranking Technique. Robust Ranking technique is used to find the expected mean queue length(Lq), Pv, and Pbusy. Further analytical results of Lq, Pv and Pbusy are numerically illustrated under crisp environment for the different values of the parameters.

References
  1. Chen, S.P (2005) “Parametric nonlinear Programming approach to fuzzy queues with bulk service”, European Journal of Operational Research, Vol.163,pp.434-444
  2. Choobinesh, F and Li, H (1993), “An index for ordering fuzzy numbers”, Fuzzy numbers and system,Vol 54, pp.143-161.
  3. Julia Rose Mary .K and Afthab Begum .M (2009),” Closed form Analytical solution of the General Bulk service queueing model M/M(a,b)/1 under working vacation”, International conference on Mathematical and Computational models, PSG College of Tech. 92-100.
  4. Julia Rose Mary .K and Angel Jenitta (2014), “Evaluation of total average cost of MX(m,N)/M/1/BD/SV with fuzzy parameter using Robust Ranking Technique”, National Annual Research Congress.
  5. Julia Rose Mary .K and Shanmugapriya (2014),“ Optional operating policy of FMX(m,N)/GSOS/1/MV”, International journal of computer Application, vol 1,issued 4,pp.199-207.
  6. Julia Rose Mary .K and Majula Christina (2015), “Evaluation of total average cost of MX(m,N)/M/1/BD/MV with fuzzy parameters using Robust Ranking Technique”, International journal of Computer Application, vol.121-No.24.,pp.1-4.
  7. Julia Rose Mary .K and Pavithra .J (2016), “Analysis of FM/M(a,b)/1/MWV queueing model. International Journal of Innovative Research in Science. Engineering and Technology. Vol.5 issue 2, pp.1391-1397.
  8. Kao, C., Li, C., and Chen,S., (1993), “Parametric programming to the analysis of fuzzy queues”, Fuzzy sets and system, vol.107, pp.93-100
  9. Li, R.J., and Lee, E.S., (1989), “Analysis of fuzzy queues, Computers and Mathematics with applications, vol.17(7), pp.1143-1147.
  10. Nagarajan & Solairaju (2010), “Computing Improved fuzzy optimal Hungarian assignment problems with fuzzy costs under Robust Ranking Techniques”, vol.6, no.13, pp.6-13.
  11. Nagi, D.S., and lee, E.S., (1992), “Analysis and simulation of fuzzy queues”, Fuzzy sets and systems, vol.46, pp.321-330.
  12. Neuts M.F., (1967), “A general class of bulk queues with poisson input”,Ann.Math.Statist., Vol.38,pp.759-770.
  13. [Nagoor Gani .A and Ashok kumar .v (2009), “A bulk arrival queueing model with fuzzy parameters and fuzzy varying batch size”, BPAS Research, vol.2,no.333.
  14. Palpandi .B, Geethamani .G (2013), “Evaluation of Performance of bulk arrival queue with fuzzy parameters using Robust Ranking Technique”, International journal of computing Engineering research, vol.03, issue 10, pp.53-57.
  15. Ritha and Lilly Robert (2009), “ Application of fuzzy set theory to queues”, International Journal of Computing and Mathematics, International Journal of Algorithms, Computing and Mathematics, vol.2, no.4.
  16. Servi, LD., and Finn, S.G., (2002) “M/M/1 queues with working vacations(M/M/1/WV)”, Performance Evauation,Vol.50,pp. 41-52, 2002.
  17. Tian, N., Zhao, X., and Wang, K., “The M/M/1 queue with single working vacation”, International Journal of Information Management Sciences, Vol.19, pp.621-634, 2008a.
  18. Tian, N., Li, J., and Zhang, G., “Matrix analytic method and working vacation queue-A survey”, International Journal of Information Management Sciences,Vol.20,pp.603-633, 2009.
  19. Yager, R.R (1981) “A Procedure for Ordering fuzzy subsets of the unit interval, Information Sciences, vol.24, pp.143-161
  20. Zadeh, (1965), “Fuzzy Sets”, Information and Control, Vol 5(3), pp:338.
  21. Zhang Z., and Xu, X., “Analysis for the M/M/1 queue with multiple working vacations and N- Policy”, Information and Management services,Vol.19(3),pp.495-506, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Multiple Working Vacation break down Mean queue length Robust Ranking Technique Fuzzy number.

Powered by PhDFocusTM