Skip to main content
Log in

Partial Pooling in Tandem Lines with Cooperation and Blocking

  • Published:
Queueing Systems Aims and scope Submit manuscript

Abstract

For a tandem line of finite, single-server queues operating under the production blocking mechanism, we study the effects of pooling several adjacent stations and the associated servers into a single station with a single team of servers. We assume that the servers are cross-trained (so that they can work at several different stations) and that two or more servers can cooperate on the same job. For such a system, we provide sufficient conditions on the service times and sizes of the input and output buffers at the pooled station under which pooling will decrease the departure time of each job from the system (and hence increase the system throughput). We also show that pooling decreases the total number of jobs in the system at any given time and the sojourn time of each job in the system if the departure time of each job from the system is decreased by pooling and there is an arrival stream at the first station. Moreover, we provide sufficient conditions under which pooling will improve the holding cost of each job in the system incurred before any given time, and extend our results to closed tandem lines and to queueing networks with either a more general blocking mechanism or probabilistic routing. Finally, we present a numerical study aimed at quantifying the improvements in system performance obtained through pooling and at understanding which stations should be pooled to achieve the maximum benefit. Our results suggest that the improvements gained by pooling may be substantial and that the bottleneck station should be among the pooled stations in order to obtain the greatest benefit.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. H. Ahn, I. Duenyas and R.Q. Zhang, Optimal stochastic scheduling of a two-stage tandem queue with parallel servers, {Advances in Applied Probability} 31(4) (1999) 1095–1117

    Google Scholar 

  2. S. Andradóttir and H. Ayhan, Throughput maximization for tandem lines with two stations and flexible servers, {Operations Research} 53(3) (2005), 516–531

    Google Scholar 

  3. S. Andradóttir, H. Ayhan and D.G. Down, Server assignment policies for maximizing the steady-state throughput of finite queueing systems, {Management Science} 47(10) (2001) 1421–1439.

    Google Scholar 

  4. S. Andradóttir, H. Ayhan and D.G. Down, Dynamic server allocation for queueing networks with flexible servers, {Operations Research} 51(6) (2003) 952–968.

    Google Scholar 

  5. N.T. Argon, Performance enhancements in tandem queueing networks and confidence interval estimation in steady-state simulations, Ph.D. Dissertation, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, (2002).

  6. J.J. Bartholdi III, D.D. Eisenstein and R.D. Foley, Performance of bucket brigades when work is stochastic, {Operations Research} {49(5)} (2001) 710–719.

    Article  Google Scholar 

  7. S. Benjaafar, Performance bounds for the effectiveness of pooling in multi-processing systems, {European Journal of Operations Research} {87(2)} (1995) 375–388.

    Article  Google Scholar 

  8. D.P. Bischak, Performance of a manufacturing module with moving workers, {IIE Transactions} {28(9)} (1996) 723–733.

    Google Scholar 

  9. J.A. Buzacott, Commonalities in reengineered business processes: Models and issues, {Management Science} {42(5)} (1996) 768–782.

    Google Scholar 

  10. J.A. Buzacott and J.G. Shanthikumar, Stochastic Models of Manufacturing Systems (Prentice Hall, Englewood Cliffs, NJ, 1993).

    Google Scholar 

  11. M. Bramson, Instability of FIFO queueing networks, {The Annals of Applied Probability} {4(2)} (1994) 414–431.

    Google Scholar 

  12. J.B. Calabrese, Optimal workload allocation in open networks of multiserver queues, {Management Science} {38(12)} (1992) 1792–1802.

    Google Scholar 

  13. C.A. Carnall and R. Wild, The location of variable work stations and the performance of production flow lines, {International Journal of Production Research} {14(6)} (1976) 703–710.

    Google Scholar 

  14. D.W. Cheng and D.D. Yao, Tandem queues with general blocking: A unified model and stochastic comparisons, {Discrete Event Dynamic Systems:} Theory and Applications {2(3/4)} (1993) 207–234.

    Google Scholar 

  15. R. Conway, W. Maxwell, J.O. McClain and L.J. Thomas, The role of work-in-process inventory in serial production lines, {Operations Research} {36(2)} (1988) 229–241.

    Google Scholar 

  16. P. Glasserman and D.D. Yao, Monotonicity in generalized semi-markov processes, {Mathematics of Operations Research} {17(1)} (1992) 1–21.

    Google Scholar 

  17. P. Glasserman and D.D. Yao, A GSMP framework for the analysis of production lines, Chapter 4 in: Stochastic Modeling and Analysis of Manufacturing Systems, ed. D.D. Yao (Springer-Verlag, New York, NY, 1994) pp. 133–188.

    Google Scholar 

  18. P. Glasserman and D.D. Yao, Structured buffer-allocation problems, {Discrete Event Dynamic Systems: Theory and Applications} 6(1) (1996) 9–41.

    Google Scholar 

  19. F.S. Hillier and R.W. Boling, The effect of some design factors on the efficiency of production lines with variable operation times, {Journal of Industrial Engineering} {17 (12)} (1966) 651–658.

    Google Scholar 

  20. F.S. Hillier, K.C. So and R.W. Boling, Notes: Toward characterizing the optimal allocation of storage space in production line systems with variable processing times, {Management Science} {39(1)} (1993) 126–133.

    Google Scholar 

  21. A. Mandelbaum and M.I. Reiman, On pooling in queueing networks, {Management Science} {44(7)} (1998) 971–981.

    Google Scholar 

  22. L.E. Meester and J.G. Shanthikumar, Concavity of the throughput of tandem queueing systems with finite buffer storage space, {Advances in Applied Probability} {22(3)} (1990) 764–767.

    Google Scholar 

  23. E.J. Muth, The production rate of a series of work stations with variable service times, {International Journal of Production Research} {11(2)} (1973) 155–169.

    Google Scholar 

  24. V.G. Kulkarni, Modeling and Analysis of Stochastic Systems (Chapman & Hall, London, UK, 1995).

    Google Scholar 

  25. H.T. Papadopoulos and M.I. Vidalis, Minimizing WIP inventory in reliable production lines, {International Journal of Production Economics} {70(2)} (2001) 185–197.

    Article  Google Scholar 

  26. M. Shaked and J.G. Shanthikumar, Stochastic Orders and Their Applications (Academic Press, San Diego, CA, 1994).

    Google Scholar 

  27. J.G. Shanthikumar and D.D. Yao, Second-order stochastic properties in queueing systems, Proceedings of the IEEE {77(1)} (1989) 162–170.

  28. D.R. Smith and W. Whitt, Resource sharing for efficiency in traffic systems, {Bell System Technical Journal} {60(1)} (1981) 39–55.

    Google Scholar 

  29. K.C. So, Optimal buffer allocation strategy for minimizing work-in-process inventory in unpaced production lines, IIE Transactions 29(1) (1997) 81–88.

    Google Scholar 

  30. D. Stoyan, Comparison Methods for Queues and Other Stochastic Models (John Wiley & Sons, New York, NY, 1983).

    Google Scholar 

  31. S.V. Tembe and R.W. Wolff, The optimal order of service in tandem queues, {Operations Research} {22(4)} (1974) 824–832.

    Google Scholar 

  32. M.P. Van Oyen, E.G.S. Gel and W.J. Hopp, Performance opportunity of workforce agility in collaborative and noncollaborative work systems, {IIE Transactions} {33(9)} (2001) 761–777.

    Article  Google Scholar 

  33. M.H. Veatch and L.M. Wein, Optimal control of a two-station production/inventory system, {Operations Research} {42(2)} (1994) 337–350.

    Google Scholar 

  34. G. Yamazaki and H. Sakasegawa, Properties of duality in tandem queueing systems, {Annals of the Institute of Statistical Mathematics} {27(2)} (1975) 201–212.

    Google Scholar 

  35. E. Zadavlav, J.O. McClain and L.J. Thomas, Self-buffering, self-balancing, self-flushing production lines, {Management Science} {42(8)} (1996) 1151–1164.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

AMS subject classification: 90B22

Rights and permissions

Reprints and permissions

About this article

Cite this article

Argon, N.T., Andradóttir, S. Partial Pooling in Tandem Lines with Cooperation and Blocking. Queueing Syst 52, 5–30 (2006). https://doi.org/10.1007/s11134-006-3101-5

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11134-006-3101-5

Keywords

Navigation