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Published in: Soft Computing 21/2019

26-11-2018 | Methodologies and Application

Interval-valued probabilistic hesitant fuzzy set for multi-criteria group decision-making

Authors: R. Krishankumar, K. S. Ravichandran, Samarjit Kar, Pankaj Gupta, Mukesh Kumar Mehlawat

Published in: Soft Computing | Issue 21/2019

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Abstract

As a powerful extension to fuzzy set, hesitant fuzzy set (HFS) attracted many scholars in the recent times. The HFS had the ability to accept multiple membership values for a specific instance, which helped in handling uncertainty to a certain extent. However, the previous studies on the hesitant fuzzy theory consider only single occurring probability value for each element which is problematic for decision-makers (DMs) to associate an accurate occurring probability with each element. To alleviate this issue, in this paper, a new concept called interval-valued probabilistic hesitant fuzzy set (IVPHFS) is proposed. Some desirable properties of IVPHFS are also investigated. Further, a new aggregation operator called simple interval-valued probabilistic hesitant fuzzy weighted geometry (SIVPHFWG) is presented and some interesting properties are discussed. Following this, a new extension of statistical variance (SV) is put forward under IVPHFS for calculating the weights of each criterion. A new extension to the popular VIKOR (VlseKriterijumskaOptimizacijaKompromisnoResenje) method is also presented under IVPHFS for ranking objects. The practicality of the proposed decision framework is analyzed by presenting two illustrative examples, viz., supplier selection problem and smartphone selection problem. Finally, the strength and weakness of the proposed decision framework are realized by comparison with other methods.

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Literature
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Metadata
Title
Interval-valued probabilistic hesitant fuzzy set for multi-criteria group decision-making
Authors
R. Krishankumar
K. S. Ravichandran
Samarjit Kar
Pankaj Gupta
Mukesh Kumar Mehlawat
Publication date
26-11-2018
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 21/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3638-3

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