#5465. Fuzzy-based EOQ model with credit financing and backorders under human learning
August 2026 | publication date |
Proposal available till | 19-05-2025 |
4 total number of authors per manuscript | 0 $ |
The title of the journal is available only for the authors who have already paid for |
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Journal’s subject area: |
Economics |
Places in the authors’ list:
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)
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.
Keywords:
Backorders; Fuzzy Environment; Human Learning; Signed Distance Method; Trade Credit Financing
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