Various aggregation operators of the generalized hesitant fuzzy numbers based on Archimedean t-norm and t-conorm functions

Garg, Harish; Keikha, Abazar

doi:10.1007/s00500-022-07516-8

Cited by 10 publications

(5 citation statements)

References 50 publications

(48 reference statements)

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“…Therefore, the proposed approach can be developed with the Z-number and R-number theories. One of the future suggestions is to use the SFS Choquet integral recommended by Bonab et al [15] to consider the relationships between the criteria when obtaining the weights of the criteria. It is also possible to use the methods developed with artificial intelligence such as the HECON method [26] to obtain the weight of the criteria in the future.…”

Section: Discussionmentioning

confidence: 99%

“…The evaluation and prioritization of alternative vehicles based on existing criteria might be considered with multi-criteria decision-making (MCDM). MCDM has been developed in the fuzzy environment due to the uncertainty in the data of real-world problems and the challenges faced when dealing with it [15][16][17]. The fuzzy set was first introduced by Zadeh, et al [18] to deal with uncertainty.…”

Section: Introductionmentioning

confidence: 99%

“…This set is an extension of neutrosophic sets (NS), intuitionistic fuzzy sets (IFS), and Pythagorean fuzzy sets (PFS). In this set, in addition to membership and non- MCDM has been developed in the fuzzy environment due to the uncertainty in the data of real-world problems and the challenges faced when dealing with it [15][16][17]. The fuzzy set was first introduced by Zadeh, et al [18] to deal with uncertainty.…”

Section: Introductionmentioning

confidence: 99%

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Assessing Sustainable Passenger Transportation Systems to Address Climate Change Based on MCDM Methods in an Uncertain Environment

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Climate change, the emission of greenhouse gases, and air pollution are some of the most important and challenging environmental issues. One of the main sources of such problems is the field of transportation, which leads to the emission of greenhouse gases. An efficient way to deal with such problems is carrying out sustainable transportation to reduce the amount of air pollution in an efficient way. The evaluation of sustainable vehicles can be considered a multi-criteria decision-making (MCDM) method due to the existence of several criteria. In this paper, we aim to provide an approach based on MCDM methods and the spherical fuzzy set (SFS) concept to evaluate and prioritize sustainable vehicles for a transportation system in Tehran, Iran. Therefore, we have developed a new integrated approach based on the stepwise weight assessment ratio analysis (SWARA) and the measurement of alternatives and ranking according to the compromise solution (MARCOS) methods in SFS to assess the sustainable vehicles based on the criteria identified by experts. The evaluation results show that the main criterion of the environment has a high degree of importance compared to other criteria. Moreover, autonomous vehicles are the best and most sustainable vehicles to reduce greenhouse gas emissions. Finally, by comparing the ranking results with other decision-making methods, it was found that the proposed approach has high validity and efficiency.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessing Sustainable Passenger Transportation Systems to Address Climate Change Based on MCDM Methods in an Uncertain Environment

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“…The idea of HFS is widely applied in several complications. Most scholars have critically investigated HF data accumulation procedures and their effects in DM [11][12][13]. Recently, Tahir et al [14] introduced the concept of an intuitionistic hesitant fuzzy set (IHFS), which is a fusion of IFS and HFS.…”

Section: Introductionmentioning

confidence: 99%

Selection of Investment Policy Using a Novel Three-Way Group Decision Model under Intuitionistic Hesitant Fuzzy Sets

et al. 2023

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In today’s fast-paced and dynamic business environment, investment decision making is becoming increasingly complex due to the inherent uncertainty and ambiguity of the financial data. Traditional decision-making models that rely on crisp and precise data are no longer sufficient to address these challenges. Fuzzy logic-based models that can handle uncertain and imprecise data have become popular in recent years. However, they still face limitations when dealing with complex, multi-criteria decision-making problems. To overcome these limitations, in this paper, we propose a novel three-way group decision model that incorporates decision-theoretic rough sets and intuitionistic hesitant fuzzy sets to provide a more robust and accurate decision-making approach for selecting an investment policy. The decision-theoretic rough set theory is used to reduce the information redundancy and inconsistency in the group decision-making process. The intuitionistic hesitant fuzzy sets allow the decision makers to express their degrees of hesitancy in making a decision, which is not possible in traditional fuzzy sets. To combine the group opinions, we introduce novel aggregation operators under intuitionistic hesitant fuzzy sets (IHFSs), including the IHF Aczel-Alsina average IHFAAA operator, the IHF Aczel-Alsina weighted average IHFAAWAϣ operator, the IHF Aczel-Alsina ordered weighted average IHFAAOWAϣ operator, and the IHF Aczel-Alsina hybrid average IHFAAHAϣ operator. These operators have desirable properties such as idempotency, boundedness, and monotonicity, which are essential for a reliable decision-making process. A mathematical model is presented as a case study to evaluate the effectiveness of the proposed model in selecting an investment policy. The results show that the proposed model is effective and provides more accurate investment policy recommendations compared to existing methods. This research can help investors and financial analysts in making better decisions and achieving their investment goals.

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“…Another approach to handling vagueness was established by Torra [10] in the form of hesitant fuzzy sets (HFSs), which expand upon the theory of FSs by allowing membership grades to hold a range of possible values within the interval of 0-1. The concept of HFSs has been widely applied across various complexities, with numerous researchers critically examining data aggregation procedures and their impact on decision-making [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

An Innovative Decision Model Utilizing Intuitionistic Hesitant Fuzzy Aczel-Alsina Aggregation Operators and Its Application

et al. 2023

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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.

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Various aggregation operators of the generalized hesitant fuzzy numbers based on Archimedean t-norm and t-conorm functions

Cited by 10 publications

References 50 publications

Assessing Sustainable Passenger Transportation Systems to Address Climate Change Based on MCDM Methods in an Uncertain Environment

Assessing Sustainable Passenger Transportation Systems to Address Climate Change Based on MCDM Methods in an Uncertain Environment

Selection of Investment Policy Using a Novel Three-Way Group Decision Model under Intuitionistic Hesitant Fuzzy Sets

An Innovative Decision Model Utilizing Intuitionistic Hesitant Fuzzy Aczel-Alsina Aggregation Operators and Its Application

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