Title: Optimisation of finite economic production quantity model under cloudy normalised triangular fuzzy number

Authors: Neelanjana Rajput; Anand Chauhan; R.K. Pandey

Addresses: Department of Mathematics, D.B.S. (P.G.) College, Rajpur Road, Dehradun, 248001, Uttarakhand, India ' Department of Applied Sciences, Graphic Era University, Bell Road, Clementown Dehradun, 248001, Uttarakhand, India ' Department of Mathematics, D.B.S. (P.G.) College, Rajpur Road, Dehradun, 248001, Uttarakhand, India

Abstract: This study introduced an economic production quantity (EPQ) model with a finite production rate established for cloudy normalised triangular fuzzy number (CNTFN). In real-life situations, the goals and inventory parameters are not precise. Such type of uncertainty may be characterised by fuzzy numbers. The main objective of this research effort is to develop a mathematical model and optimise EPQ with different environment-like crisp, general fuzzy and cloudy fuzzy situations. A novel defuzzification methodology has been used for EPQ by Yager's ranking index method. Here, the constraint goal and the inventory cost parameters are assumed to be triangular-shaped fuzzy numbers with different types of left and right membership functions. The cost functions associated to these models are verified to be convex, and optimal criteria are established in all three situations. The models are numerical, graphically demonstrated and sensitivity analysis shows a decent explanation. The paper also discusses the applications and future scope of the CNTFN model in realistic situations such as when items are not easy to replenish due to some transport problem and some problems in geographically hilly regions.

Keywords: fuzzy optimisation; decision making; cloud fuzzy number; EPQ inventory model; finite production; extended Yager's ranking index method.

DOI: 10.1504/IJOR.2022.121485

International Journal of Operational Research, 2022 Vol.43 No.1/2, pp.168 - 187

Received: 26 Nov 2019
Accepted: 09 May 2020
Published online: 16 Mar 2022 *

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