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Random Demand Satisfaction in Unreliable Production–Inventory–Customer Systems

Author

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  • Jingshan Li
  • Emre Enginarlar
  • Semyon Meerkov

Abstract

A method for calculating the probability of customer demand satisfaction in production–inventory–customer systems with Markovian machines, finite finished goods buffers, and random demand is developed. Using this method, the degradation of this probability as a function of demand variability is quantified. In addition, it is shown by examples that the probability of customer demand satisfaction depends primarily on the coefficient of variation, rather than on the complete distribution, of the demand. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Jingshan Li & Emre Enginarlar & Semyon Meerkov, 2004. "Random Demand Satisfaction in Unreliable Production–Inventory–Customer Systems," Annals of Operations Research, Springer, vol. 126(1), pages 159-175, February.
    • Handle: RePEc:spr:annopr:v:126:y:2004:i:1:p:159-175:10.1023/b:anor.0000012279.78938.6b
    DOI: 10.1023/B:ANOR.0000012279.78938.6b
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    Cited by:

    1. Shib Sana, 2015. "An EOQ model for stochastic demand for limited capacity of own warehouse," Annals of Operations Research, Springer, vol. 233(1), pages 383-399, October.
    2. Yihai He & Changchao Gu & Xiao Han & Jiaming Cui & Zhaoxiang Chen, 2017. "Mission reliability modeling for multi-station manufacturing system based on Quality State Task Network," Journal of Risk and Reliability, , vol. 231(6), pages 701-715, December.
    3. Jiarong Luo & Xu Chen, 2017. "Risk hedging via option contracts in a random yield supply chain," Annals of Operations Research, Springer, vol. 257(1), pages 697-719, October.

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