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Inventory policies under fuzzy and cloud fuzzy environment

Inventory policies under fuzzy and cloud fuzzy environment This article is an attempt to extend the classical economic order quantity (EOQ) model for deteriorating items under fuzzy and cloud fuzzy environment. Inventory parameters such as holding cost, purchase cost, ordering cost, demand rate and deterioration rate are considered as triangular fuzzy numbers as well as cloud triangular fuzzy numbers to develop fuzzy and cloud fuzzy models respectively. Yager's ranking method and De and Beg's ranking methods are used for defuzzification. A comparative study reveals the superiority of cloud fuzzy model over crisp and fuzzy model. Further, numerical example, graphical illustrations and sensitivity analysis are carried out for better understanding of the application of cloud fuzzy approach to inventory optimisation problem. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Information and Decision Sciences Inderscience Publishers

Inventory policies under fuzzy and cloud fuzzy environment

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1756-7017
eISSN
1756-7025
DOI
10.1504/ijids.2022.127459
Publisher site
See Article on Publisher Site

Abstract

This article is an attempt to extend the classical economic order quantity (EOQ) model for deteriorating items under fuzzy and cloud fuzzy environment. Inventory parameters such as holding cost, purchase cost, ordering cost, demand rate and deterioration rate are considered as triangular fuzzy numbers as well as cloud triangular fuzzy numbers to develop fuzzy and cloud fuzzy models respectively. Yager's ranking method and De and Beg's ranking methods are used for defuzzification. A comparative study reveals the superiority of cloud fuzzy model over crisp and fuzzy model. Further, numerical example, graphical illustrations and sensitivity analysis are carried out for better understanding of the application of cloud fuzzy approach to inventory optimisation problem.

Journal

International Journal of Information and Decision SciencesInderscience Publishers

Published: Jan 1, 2022

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