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Average cost per unit time control of stochastic manufacturing systems: Revisited

Author

Listed:
  • T. E. Duncan
  • B. Pasik-Duncan
  • Ł. Stettner

Abstract

An optimal production planning for a stochastic manufacturing system is considered. The system consists of a single, failure-prone machine that produces a finite number of different products. The objective is to determine a rate of production that minimizes an average cost per unit time criterion where the demand is random. The results given in this paper are based on some large deviation estimates and the Hamilton-Jacobi-Bellman equations for convex functions. Copyright Springer-Verlag Berlin Heidelberg 2001

Suggested Citation

  • T. E. Duncan & B. Pasik-Duncan & Ł. Stettner, 2001. "Average cost per unit time control of stochastic manufacturing systems: Revisited," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 54(2), pages 259-278, December.
    • Handle: RePEc:spr:mathme:v:54:y:2001:i:2:p:259-278
    DOI: 10.1007/s001860100146
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    Cited by:

    1. S. P. Sethi & H. Yan & H. Zhang & Q. Zhang, 2002. "Optimal and Hierarchical Controls in Dynamic Stochastic Manufacturing Systems: A Survey," Manufacturing & Service Operations Management, INFORMS, vol. 4(2), pages 133-170.

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