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Granular Computing
Published in: Granular Computing 4/2018

11-12-2017 | Original Paper

Possibility–necessity–credibility measures on generalized intuitionistic fuzzy number and their applications to multi-product manufacturing system

Authors: Totan Garai, Dipankar Chakraborty, Tapan Kumar Roy

Published in: Granular Computing | Issue 4/2018

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Abstract

As a special intuitionistic fuzzy set on a real number set, intuitionistic fuzzy numbers (IFNs) have the best capability to model ill-known quantities. The purpose of this paper is to investigate generalized intuitionistic fuzzy numbers (GIFNs). The weighted possibility, necessity and credibility measures of generalized trapezoidal intuitionistic fuzzy numbers (GTIFN) are introduced, and expected value of GTIFN has been formulated. By employing the possibility and necessity measures of GIFN, the single period multi-product manufacturing generalized intuitionistic fuzzy inventory models is transformed into an equivalent deterministic problem. The transformed problem has been solved by soft computing technique. Finally, the proposed method is illustrated with one numerical example.
previous article A fuzzy compromise programming model based on the modified S-curve membership functions for supplier selection
next article A unified method of defuzzification for type-2 fuzzy numbers with its application to multiobjective decision making

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Metadata
Title
Possibility–necessity–credibility measures on generalized intuitionistic fuzzy number and their applications to multi-product manufacturing system
Authors
Totan Garai
Dipankar Chakraborty
Tapan Kumar Roy
Publication date
11-12-2017
Publisher
Springer International Publishing
Published in
Granular Computing / Issue 4/2018
Print ISSN: 2364-4966
Electronic ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-017-0067-0

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