Title: Fuzzy inventory modelling: addressing uncertainty in economic order quantity analysis within nonlinear science

Authors: Soumendra Kumar Patra; Pragyan Parimita Sarangi; Nirmal Kumar Routra; Alok Kumar Jagadev; Bijay Kumar Paikaray

Addresses: Department of Business Administration, Ravenshaw University, Cuttack, Odisha, 753003, India ' Department of Management, Srusti Academy of Management (Autonomous), Bhubaneswar, Odisha, 751024, India ' Department of Business Management, Fakir Mohan University, Balasore, Odisha, 756020, India ' School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, 751024, India ' Centre for Data Science, Department of Computer Science and Engineering, Siksha 'O' Anusandhan (Deemed to be) University, Bhubaneswar, Odisha, 751030, India

Abstract: Generally, in deriving the solution of economic order quantity (EOQ) inventory model, we consider deterioration rate, holding cost and ordering cost as constant. But in the case of real life problems, the above case is not actually constant but slightly disturbed from their original crisp value. In this paper, fuzzy inventory model is developed considering deterioration rate, holding cost and ordering cost as fuzzy variables. Since in practice, it is not always easy to determine the rate of deterioration precisely. In most of the cases it is uncertain in nature; therefore, it becomes reasonable to consider the vagueness and uncertainty of deterioration rate in fuzzy environment. These variables are represented by trapezoidal membership function. The function principle is applied to obtain an optimum total fuzzy cost along with optimum order quantity and optimum shortage quantity.

Keywords: fuzzy membership function; fuzzy deterioration rate; trapezoidal numbers; function principle; defuzzification.

DOI: 10.1504/IJANS.2024.146654

International Journal of Applied Nonlinear Science, 2024 Vol.4 No.4, pp.308 - 321

Received: 27 Apr 2024
Accepted: 06 Jul 2024
Published online: 11 Jun 2025 *

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