Title: An EOQ model based on intuitionistic fuzzy and cloudy intuitionistic fuzzy demand rate

Authors: Surendra Singh; Tanuj Kumar

Addresses: Department of Mathematics, SRM Institute of Science and Technology, NCR Campus, Ghaziabad, Uttar Pradesh, 201204, India ' Department of Mathematics, SRM Institute of Science and Technology, NCR Campus, Ghaziabad, Uttar Pradesh, 201204, India

Abstract: This article described a classical EOQ inventory model under intuitionistic fuzzy and cloudy intuitionistic fuzzy demand rates. It is generally assumed that the uncertainty of the parameters of an inventory model is constant over time, but in reality, the uncertainty tends to decrease over time as the business of company grows in market. This study looks up the cloudy intuitionistic fuzzy number to address such type of uncertainty. At first glance, we formulate a crisp EOQ inventory model and then it is fuzzified to archiving decisions under the intuitionistic fuzzy as well as the cloudy intuitionistic fuzzy demand rate. Further, to solve an intuitionistic and cloudy intuitionistic fuzzy models, we develop two new defuzzification formulas based on Yager's indexing method and De and Beg's index method, respectively. Finally, a comparative analysis between the crisp, intuitionistic fuzzy and cloudy intuitionistic fuzzy models for the optimal values of average inventory cost, inventory level and cycle length is illustrated with the help of numerical example. The article is finally concluded with scope for possible future work.

Keywords: EOQ model; triangular intuitionistic fuzzy numbers; cloudy intuitionistic fuzzy number; total average inventory cost; defuzzification; degree of fuzziness.

DOI: 10.1504/IJSOM.2024.143063

International Journal of Services and Operations Management, 2024 Vol.49 No.3, pp.360 - 378

Received: 11 May 2022
Accepted: 04 Sep 2022
Published online: 03 Dec 2024 *

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