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A fuzzy random continuous review inventory system

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  • Dey, Oshmita
  • Chakraborty, Debjani

Abstract

A fuzzy random continuous review system has been presented in this paper with the annual customer demand assumed to be a uniformly distributed continuous fuzzy random variable. Besides the reorder point and the production lot size, the setup cost and the 'out of control' probability for a production process have been assumed to be control parameters in the model. Investments to reduce the setup cost and improve the process quality have been incorporated into the total cost in this regard. A methodology has been proposed to minimize this cost and it has been illustrated by way of a numerical example.

Suggested Citation

  • Dey, Oshmita & Chakraborty, Debjani, 2011. "A fuzzy random continuous review inventory system," International Journal of Production Economics, Elsevier, vol. 132(1), pages 101-106, July.
    • Handle: RePEc:eee:proeco:v:132:y:2011:i:1:p:101-106
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    References listed on IDEAS

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    Cited by:

    1. Totan Garai & Dipankar Chakraborty & Tapan Kumar Roy, 2019. "Multi-objective Inventory Model with Both Stock-Dependent Demand Rate and Holding Cost Rate Under Fuzzy Random Environment," Annals of Data Science, Springer, vol. 6(1), pages 61-81, March.
    2. Oshmita Dey, 2019. "A fuzzy random integrated inventory model with imperfect production under optimal vendor investment," Operational Research, Springer, vol. 19(1), pages 101-115, March.
    3. Ravi Shankar Kumar & M. K. Tiwari & A. Goswami, 2016. "Two-echelon fuzzy stochastic supply chain for the manufacturer–buyer integrated production–inventory system," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 875-888, August.

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