Annals of Operations Research

, Volume 17, Issue 1, pp 233–248 | Cite as

Optimal control rules for scheduling job shops

  • Sheldon X. C. Lou
  • Garrett Van Ryzin
Chapter 3 Production Scheduling


In this paper, we develop the control rules for job shop scheduling based on theFlow Rate Control model. We derive optimal control results for job shops with work station in series (transfer line). We use these results to derive rules which are suboptimal, robust against random events, and easy to implement and expand.


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  1. [1]
    J.H. Blackstone Jr, D.T. Phillips and G.L. Hogg, A state-of-the art survey of dispatching rules for manufacturing job shop operations, Int. J. Prod. Res. 20, No. 1 (1982) 27–345.Google Scholar
  2. [2]
    R.W. Conway, W.L. Maxwell and L.W. Miller,Theory of Scheduling (Addison-Wesley, Reading, Mass., 1967).Google Scholar
  3. [3]
    M. Fox, Constraint-directed search: a case study of job-shop scheduling, Ph. D. Thesis, Carnegie-Mellon University, 1983.Google Scholar
  4. [4]
    S.C. Graves, A tractical planning model for a job shop, Working Paper, Alfred P. Sloan School of Management, MIT, 1985.Google Scholar
  5. [5]
    E.W. Lawler, Recent results in the theory of machine scheduling.Google Scholar
  6. [6]
    J. Kimemia and S.B. Gershwin, An algorithm for the computer control of a flexible manufacturing system, IIE Transactions, 15, No. 4 (December 1983) 353–362.Google Scholar
  7. [7]
    J.K. Lenstra, Sequencing by enumerative methods, Mathematical centre Tract 69, Mathematisch Centrum, Amsterdam, 1977.Google Scholar
  8. [8]
    S.X.C. Lou, G. Van Ryzin and S.B. Gershwin, Scheduling job shops with delays,Proc. IEEE International Conf. on Robotics and Automation, Raleigh, North Carolina, March, 1987.Google Scholar
  9. [9]
    S.X.C. Lou, Job shop scheduling using flow rate control, M.I.T. Laboratory for Information and Decision Systems, LIPS-P-1618, September, 1986.Google Scholar
  10. [10]
    S.B. Gershwin, R. Akella and Y.F. Choong, Short-term production scheduling of an automated manufacturing facility, IBM Journal of Research and Development, Vol. 29, No. 4 (July 1985) 392–400.Google Scholar
  11. [11]
    R. Akella, Y.F. Choong and S.B. Gershwin, Performance of Hierarchical production scheduling policy, IEEE Transactions on Components, Hybrids, and Manufacturing Technology, Vol. CHMT-7, No. 3 (September 1984).Google Scholar
  12. [12]
    R. Akella and P.R. Kumar, Optimal control of production rate in failure prone manufacturing system, IEEE Trans. on Automatic Control, Vol. AC-31, No. 2 (February 1986) 116–126.Google Scholar
  13. [13]
    T. Bielicki and P.R. Kumar, Optimality of zero-inventory policies for unreliable manufacturing systems (1987).Google Scholar
  14. [14]
    S.C. Graves, H.C. Meal, D. Stefek and A.H. Zeghmi, Scheduling of re-entrant flow shops, Journal of Operations Management, Vol. 3, No. 4 (August 1983) 197–207.Google Scholar
  15. [15]
    G. Van Ryzin, Control of manufacturing systems with delays, M.S. Thesis under preparation, Laboratory for Information and Decision Systems, MIT.Google Scholar
  16. [16]
    D.P. Bertsekas,Dynamic Programming: Deterministic and Stochastic Models (Prentice-Hall, Inc., 1987).Google Scholar
  17. [17]
    S.E. Dreyfus and A.M. Law,The Art and Theory of Dynamic Programming (Academic Press, New York, 1977).Google Scholar
  18. [18]
    R.A. Howard,Dynamic Programming and Markow Processes (MIT Press, Cambridge, Massachusetts, 1960).Google Scholar

Copyright information

© J.C. Baltzer A.G. Scientific Publishing Company 1989

Authors and Affiliations

  • Sheldon X. C. Lou
    • 1
  • Garrett Van Ryzin
    • 2
  1. 1.Laboratory for Information and Decision SystemsMassachusetts Institute of TechnologyCambridgeU.S.A.
  2. 2.AT & T Bell LabsU.S.A.

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