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Optimal Production Policy in a Stochastic Manufacturing System

In: Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems

Author

Listed:
  • Yongjiang Guo

    (The Chinese Academy of Sciences)

  • Hanqin Zhang

    (The Chinese Academy of Sciences)

Abstract

This paper is concerned with the optimal production planning in a dynamic stochastic manufacturing system consisting of a single or parallel machines that are failure prone and facing a constant demand. The objective is to choose the production rate over time to minimize the long-run average cost of production and surplus. The analysis is developed by the infinitesimal perturbation approach. The infinitesimal perturbation analysis and identification algorithms are used to estimate the optimal threshold value. The asymptotically optimal threshold value and the convergence rate of the identification algorithms are obtained. Furthermore, the central limit theorem of the identification algorithms is also established.

Suggested Citation

  • Yongjiang Guo & Hanqin Zhang, 2006. "Optimal Production Policy in a Stochastic Manufacturing System," International Series in Operations Research & Management Science, in: Houmin Yan & George Yin & Qing Zhang (ed.), Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems, chapter 0, pages 141-157, Springer.
    • Handle: RePEc:spr:isochp:978-0-387-33815-6_8
    DOI: 10.1007/0-387-33815-2_8
    as

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