Hesitant Fuzzy Set and Its Variants for Multi-Attribute Decision-Making

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".

Deadline for manuscript submissions: 30 December 2024 | Viewed by 1576

Special Issue Editors


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Guest Editor
Information Technology Systems and Analytics Area, Indian Institute of Management Bodh Gaya, Bodh Gaya 824234, Bihar, India
Interests: fuzzy set; data-driven decision model

Special Issue Information

Dear Colleagues,

In order to overcome the limitations of classical fuzzy set, Torra (2010) developed a set called “hesitant fuzzy set (HFS)” that could accept more than one membership grade from agents and provides a flexible preference style to agents for expressing their views/opinions in a more sensible and rational manner. Driven by the flexibility, the HFS gained popularity in the field of multi-attribute decision-making (MADM) and researchers developed novel theories and practical applications with HFS (Xu and Zhang, 2019; Rodriguez et al., 2014). As the popularity increased for HFS owing to its flexibility, some interesting variants of HFS were also proposed by researchers. All these fuzzy sets primarily focused on modeling uncertainty in a rational manner.

In the same line, sustainability and green practices are gaining abundant attention in recent times by researchers around the world. Due to the urgent need for controlling carbon trace and combating climate change, the consideration for sustainability adoption and implementation has grown massively (Kissenger and Rees, 2010). It is worth noting that there are uncertainties that exist in the system, which are implicit and integral, and there is an urge for better modeling the same to better develop sustainable systems to foster growth globally. In this vein, the integration of HFS to sustainability applications could prove effective as researchers can gain flexibility to model uncertainty in the sustainability and green applications. Researchers from the field of fuzzy mathematics can actively collaborate with sustainable scientists and researchers to better model the uncertainties that exist in the system and provide readers with frameworks that could facilitate MADM in the sustainability domain.

To achieve the above goal, this proposal is put forward, which could ignite the thought in the minds of researchers and enable quality research and practical guidelines for better implementation of sustainability in the global arena. The proposal accepts research as well as review articles in the topic of concern. The proposal focuses on the following keywords (but not limited to):

  • hesitant fuzzy set and variants
  • probabilistic hesitant fuzzy set and variants
  • dual hesitant fuzzy set
  • decision approaches
  • linguistic variants of hesitant fuzzy set
  • sustainability aspects
  • green habits and carbon neutrality
  • sustainable transport
  • sustainable technological drive.

Dr. Raghunathan Krishankumar
Prof. Dr. Samarjit Kar
Guest Editors

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Published Papers (1 paper)

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Research

22 pages, 2186 KiB  
Article
An Innovative Decision Model Utilizing Intuitionistic Hesitant Fuzzy Aczel-Alsina Aggregation Operators and Its Application
by Wajid Ali, Tanzeela Shaheen, Hamza Ghazanfar Toor, Faraz Akram, Md. Zia Uddin and Mohammad Mehedi Hassan
Mathematics 2023, 11(12), 2768; https://doi.org/10.3390/math11122768 - 19 Jun 2023
Cited by 5 | Viewed by 1069
Abstract
The intuitionistic hesitant fuzzy set is a significant extension of the intuitionistic fuzzy set, specifically designed to address uncertain information in decision-making challenges. Aggregation operators play a fundamental role in combining intuitionistic hesitant fuzzy numbers into a unified component. This study aims to [...] Read more.
The intuitionistic hesitant fuzzy set is a significant extension of the intuitionistic fuzzy set, specifically designed to address uncertain information in decision-making challenges. Aggregation operators play a fundamental role in combining intuitionistic hesitant fuzzy numbers into a unified component. This study aims to introduce two novel approaches. Firstly, we propose a three-way model for investors in the business domain, which utilizes interval-valued equivalence classes under the framework of intuitionistic hesitant fuzzy information. Secondly, we present a multiple-attribute decision-making (MADM) method using various aggregation operators for intuitionistic hesitant fuzzy sets (IHFSs). These operators include the IHF Aczel–Alsina average (IHFAAA) operator, the IHF Aczel–Alsina weighted average (IHFAAWAϣ) operator, and the IHF Aczel–Alsina ordered weighted average (IHFAAOWAϣ) operator and the IHF Aczel–Alsina hybrid average (IHFAAHAϣ) operators. We demonstrate the properties of idempotency, boundedness, and monotonicity for these newly established aggregation operators. Additionally, we provide a detailed technique for three-way decision-making using intuitionistic hesitant fuzzy Aczel–Alsina aggregation operators. Furthermore, we present a numerical case analysis to illustrate the pertinency and authority of the esteblished model for investment in business. In conclusion, we highlight that the developed approach is highly suitable for investment selection policies, and we anticipate its extension to other fuzzy information domains. Full article
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