Skip to main content
Log in

Control and scheduling in a two-station queueing network: Optimal policies and heuristics

  • Published:
Queueing Systems Aims and scope Submit manuscript

Abstract

Consider a two-station queueing network with two types of jobs: type 1 jobs visit station 1 only, while type 2 jobs visit both stations in sequence. Each station has a single server. Arrival and service processes are modeled as counting processes with controllable stochastic intensities. The problem is to control the arrival and service processes, and in particular to schedule the server in station 1 among the two job types, in order to minimize a discounted cost function over an infinite time horizon. Using a stochastic intensity control approach, we establish the optimality of a specific stationary policy, and show that its value function satisfies certain properties, which lead to a switching-curve structure. We further classify the problem into six parametric cases. Based on the structural properties of the stationary policy, we establish the optimality of some simple priority rules for three of the six cases, and develop heuristic policies for the other three cases.

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. M. Bartroli, On the structure of optimal control policies for networks of queues, Ph.D. Dissertation, Department of Operations Research, University of North Carolina, Chapel Hill, NC 27514 (1989).

    Google Scholar 

  2. M. Bartroli and S. Stidham, Towards a unified theory of structure of optimal policies for control of networks of queues, Technical Report, Department of Operations Research, University of North Carolina, Chapel Hill, NC 27514 (1987).

    Google Scholar 

  3. P. Brémaud,Point Processes and Queues (Springer, New York, 1981).

    Google Scholar 

  4. H. Chen, Optimal intensity control of a multi-class queue, Queueing Syst. 5 (1989) 281–294.

    Google Scholar 

  5. H. Chen and D.D. Yao, Optimal intensity control of a queueing system with state-dependent capacity limit, IEEE Trans. Auto. Contr. AC-35 (1990) 459–464.

    Google Scholar 

  6. P. Glasserman and D.D. Yao, Monotone optimal control of permutable queueing systems, Math. Oper. Res. 19 (1994) 449–476.

    Google Scholar 

  7. J.M. Harrison,Brownian Motion and Stochastic Flow Systems (Wiley, New York, 1985).

    Google Scholar 

  8. J.M. Harrison, Brownian models of queueing networks with heterogeneous customer populations, in:Stochastic Differential Systems, Stochastic Control Theory and Applications, eds. W. Fleming and P.L. Lions, IMA Vol. 10 (Springer, New York, 1988).

    Google Scholar 

  9. J.M. Harrison and L.M. Wein, Scheduling networks of queues: Heavy traffic analysis of a simple open network, Queueing Syst. 5 (1989) 265–280.

    Google Scholar 

  10. B. Hajek, Optimal control of two interacting service stations, IEEE Trans. Auto. Contr. AC-29 (1984) 491–499.

    Google Scholar 

  11. L. Li, A stochastic model of production firms, Math. Oper. Res. 13 (1988) 447–466.

    Google Scholar 

  12. Z. Rosberg, P. Varaiya and J. Walrand, Optimal control of service in tandem queues, IEEE Trans. Auto. Contr. AC-27 (1982) 600–609.

    Google Scholar 

  13. S. Ross,Stochastic Processes (Wiley, New York, 1983).

    Google Scholar 

  14. R. Serfozo, An equivalence between discrete- and continuous-time Markov decision processes, Oper. Res. 27 (1979) 616–620.

    Google Scholar 

  15. R. Serfozo, Optimal control of random walks, birth and death processes, and queues, Adv. Appl. Prob. 13 (1981) 61–83.

    Google Scholar 

  16. S. Stidham, Optimal control of admission to a queueing system, IEEE Trans. Auto. Contr. AC-30 (1985) 705–713.

    Google Scholar 

  17. S. Stidham, Scheduling, routing and flow control in stochastic networks, in:Stochastic Differential Systems, Stochastic Control Theory and Applications, eds. W. Flemming and P.L. Lions, IMA Vol. 10 (Springer, New York, 1988).

    Google Scholar 

  18. S. Stidham and R.R. Weber, Monotonic and insensitive optimal policies for control of queues with undiscounted costs, Oper. Res. 37 (1989) 611–625.

    Google Scholar 

  19. D.M. Topkis, Minimizing a submodular function on a lattice, Oper. Res. 26 (1978) 305–321.

    Google Scholar 

  20. M.H. Veatch and L.M. Wein, Monotone control of queueing and production/inventory systems, Queueing Syst. 12 (1992) 391–408.

    Google Scholar 

  21. J. Walrand,An Introduction to Queueing Networks (Prentice-Hall, Englewood Cliffs, NJ, 1988).

    Google Scholar 

  22. R.R. Weber and S. Stidham, Optimal control of service rates in network of queues, Adv. Appl. Prob. 19 (1987) 202–218.

    Google Scholar 

  23. L.M. Wein, Optimal control of a two-station Brownian network, Math. Oper. Res. 15 (1990) 215–242.

    Google Scholar 

  24. L.M. Wein, Scheduling networks of queues: Heavy traffic analysis of a two-station network with controllable inputs, Oper. Res. 38 (1990) 1065–1078.

    Google Scholar 

  25. P. Whittle,Optimization Over Time (Wiley, New York, 1983).

    Google Scholar 

  26. P. Yang, Pathwise solutions for a class of linear stochastic systems, Ph.D. Dissertation, Department of Operations Research, Stanford University, Stanford, CA (1988).

    Google Scholar 

  27. A.A. Yushkevich, Controlled Markov models with countable state space and continuous time, Theory Prob. Appl. 22 (1977) 215–235.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, H., Yang, P. & Yao, D.D. Control and scheduling in a two-station queueing network: Optimal policies and heuristics. Queueing Syst 18, 301–332 (1994). https://doi.org/10.1007/BF01158766

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01158766

Keywords

Navigation