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Stabilizing Batch-Processing Networks

Author

Listed:
  • J. G. Dai

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205)

  • Caiwei Li

    (Oracle, 300 Oracle Parkway, Room 1084, Redwood City, California 94065)

Abstract

In a batch-processing network, multiple jobs can be formed into a batch to be processed in a single service operation. The network is multiclass in that several job classes may be processed at a server. Jobs in different classes cannot be mixed into a single batch. A batch policy specifies which class of jobs is to be served next. Throughput of a batch-processing network depends on the batch policy used. When the maximum batch sizes are equal to one, the corresponding network is called a standard-processing network, and the corresponding service policy is called a dispatch policy. There are many dispatch policies that have been proven to maximize the throughput in standard networks. This paper shows that any normal dispatch policy can be converted into a batch policy that preserves key stability properties. Examples of normal policies are given. These include static buffer priority (SBP), first-in-first-out (FIFO), and generalized round robin (GRR) policies.

Suggested Citation

  • J. G. Dai & Caiwei Li, 2003. "Stabilizing Batch-Processing Networks," Operations Research, INFORMS, vol. 51(1), pages 123-136, February.
  • Handle: RePEc:inm:oropre:v:51:y:2003:i:1:p:123-136
    DOI: 10.1287/opre.51.1.123.12802
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    References listed on IDEAS

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    1. J. G. Dai & G. Weiss, 1996. "Stability and Instability of Fluid Models for Reentrant Lines," Mathematics of Operations Research, INFORMS, vol. 21(1), pages 115-134, February.
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    Cited by:

    1. Zhao, Yaping & Xu, Xiaoyun & Li, Haidong & Liu, Yanni, 2016. "Prioritized customer order scheduling to maximize throughput," European Journal of Operational Research, Elsevier, vol. 255(2), pages 345-356.
    2. J. G. Dai & O. B. Jennings, 2004. "Stabilizing Queueing Networks with Setups," Mathematics of Operations Research, INFORMS, vol. 29(4), pages 891-922, November.

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