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Fuzzy-Based EOQ Model With Credit Financing and Backorders Under Human Learning

Author

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  • Mahesh Kumar Jayaswal

    (Banasthali Vidyapith, India)

  • Mandeep Mittal

    (AIAS, Amity University, Noida, India)

  • Isha Sangal

    (Banasthali Vidyapith, India)

  • Jayanti Tripathi

    (Amity University, Noida, India)

Abstract

In this paper, an inventory model has been developed with trade credit financing and back orders under human learning. In this model, it is considered that the seller provides a credit period to his buyer to settle the account and the buyer accepts the credit period policy with certain terms and conditions. The impact of learning and credit financing on the size of the lot and the corresponding cost has been presented. For the development of the model, demand and lead times have been taken as the fuzzy triangular numbers are fuzzified, and then learning has been done in the fuzzy numbers. First of all, the consideration of constant fuzziness is relaxed, and then the concept of learning in fuzzy under credit financing is joined with the representation, assuming that the degree of fuzziness reduces over the planning horizon. Finally, the expected total fuzzy cost function is minimized with respect to order quantity and number of shipments under credit financing and learning effect. Lastly, sensitive analysis has been presented as a consequence of some numerical examples.

Suggested Citation

  • Mahesh Kumar Jayaswal & Mandeep Mittal & Isha Sangal & Jayanti Tripathi, 2021. "Fuzzy-Based EOQ Model With Credit Financing and Backorders Under Human Learning," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 10(4), pages 14-36, October.
  • Handle: RePEc:igg:jfsa00:v:10:y:2021:i:4:p:14-36
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