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Fuzzy EOQ models with ramp type demand rate, partial backlogging and time dependent deterioration rate

Author

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  • Ravi Shankar Kumar
  • S.K. De
  • A. Goswami

Abstract

In this study, a fuzzy inventory model has been discussed for two cases: model start with no shortages; model start with shortages. Demand rate is of three folded ramp-type time dependent, deterioration rate of the item is time dependent(Weibull) and shortages are partially backlogged. For real situation, we have assumed the backlogging rate and all the cost coefficients as trapezoidal fuzzy number and defuzzification is made with the help of Function Principle and Graded Mean Integration Representation (GMIR) method. Finally using calculus, we have optimised the total cost function. The solution procedure is illustrated with the help of numerical examples.

Suggested Citation

  • Ravi Shankar Kumar & S.K. De & A. Goswami, 2012. "Fuzzy EOQ models with ramp type demand rate, partial backlogging and time dependent deterioration rate," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 4(5), pages 473-502.
    • Handle: RePEc:ids:ijmore:v:4:y:2012:i:5:p:473-502
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    Citations

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    Cited by:

    1. K. F. Mary Latha & R. Uthayakumar, 2017. "A two-echelon supply chain coordination with quantity discount incentive for fixed lifetime product in a fuzzy environment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1194-1208, November.
    2. De, Sujit Kumar & Sana, Shib Sankar, 2013. "Fuzzy order quantity inventory model with fuzzy shortage quantity and fuzzy promotional index," Economic Modelling, Elsevier, vol. 31(C), pages 351-358.
    3. Sujit De & Shib Sana, 2015. "Backlogging EOQ model for promotional effort and selling price sensitive demand- an intuitionistic fuzzy approach," Annals of Operations Research, Springer, vol. 233(1), pages 57-76, October.

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