2022
DOI: 10.31387/oscm0500350
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Inventory Modelling for technology generation products under uncertain trade credit terms and imprecise procurement costs

Gaurav Nagpal,
Udayan Chanda,
Alok Kumar
et al.

Abstract: The inventory policies for any product under the trade credit mechanism are influenced by the procurement price per unit and the credit period offered by the seller to the buyer. This paper develops an inventory model for the technology generations under the imprecise trade credit period and the imprecise procurement cost. It considers the demand that is credit-linked and governed by innovation diffusion as well. The imprecise nature of the parameters is captured by the use of fuzzy numbers. The trapezoidal me… Show more

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Cited by 1 publication
(1 citation statement)
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“…Garai et al [25] derived the possibility, necessity, and credibility measures to determine the chances of occurrence of fuzzy events while modeling inventory for multiple items. Nagpal et al [26] fuzzified the demand rate and the deterioration rate as trapezoidal membership function and used the Centroid method and signed distance method to de-fuzzify the cost function. Garai et al [27] used trapezoidal fuzzy numbers to define the time varying inventory holding cost and the price-dependent demand and developed a fully fuzzy inventory model, treating all the input parameters and decision variables as imprecise.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Garai et al [25] derived the possibility, necessity, and credibility measures to determine the chances of occurrence of fuzzy events while modeling inventory for multiple items. Nagpal et al [26] fuzzified the demand rate and the deterioration rate as trapezoidal membership function and used the Centroid method and signed distance method to de-fuzzify the cost function. Garai et al [27] used trapezoidal fuzzy numbers to define the time varying inventory holding cost and the price-dependent demand and developed a fully fuzzy inventory model, treating all the input parameters and decision variables as imprecise.…”
Section: Literature Reviewmentioning
confidence: 99%