Entropy of interval-valued intuitionistic hesitant fuzzy set and its application to group decision making problems

Joshi, Dheeraj Kumar; Kumar, Sanjay

doi:10.1007/s41066-018-0077-6

Cited by 31 publications

(11 citation statements)

References 58 publications

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“…e group decision-making problem arises in many realworld decision-making situations [72][73][74][75]. In MCGDM problems, the essence is how to effectively aggregate individual preferences into a group consensus.…”

Section: Related Workmentioning

confidence: 99%

A Revised Grey Relational Analysis Method for Multicriteria Group Decision-Making with Expected Utility Theory for Oil Spill Emergency Management

2021

Mathematical Problems in Engineering

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The substantial importance and complexity of oil spill emergency management have been confirmed by the massive, disastrous oil spill accidents that have occurred in recent years. The goal of this study is to research and develop an effective new model to accurately respond to oil spill emergencies for the purpose of disaster risk reduction. In this model, firstly, grey relational analysis is used to treat the variable and complex environment of an oil spill. Secondly, a revised grey relational analysis method based on the concept of angle between two vectors is presented to optimize assessment accuracy by measuring the similarity between the reference series and alternative series. Thirdly, by incorporating expected utility theory, a revised grey relational analysis for facilitating consensus is developed for multicriteria group decision-making. Finally, an empirical study on oil spill emergency management is discussed to demonstrate the feasibility and effectiveness of the proposed model for oil spill emergency management in a complex environment to reduce disaster risk.

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Section: Related Workmentioning

confidence: 99%

A Revised Grey Relational Analysis Method for Multicriteria Group Decision-Making with Expected Utility Theory for Oil Spill Emergency Management

2021

Mathematical Problems in Engineering

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“…Entropy method is the concept of thermodynamics, which was first introduced by Shannon into the information theory, and now is widely used in the engineering, socio-economic and other fields [22]. Entropy measures are useful in computing weights of the criteria, and had been used widely in MCGDM problems [23]. Shannon entropy method constitutes one of the techniques to determine the weight of the criteria when it becomes difficult to be provided by the decision-maker [24].…”

Section: The Determination Of the Objective Weights Based On Entropy mentioning

confidence: 99%

Probabilistic Linguistic Aggregation Operators Based on Einstein t-Norm and t-Conorm and Their Application in Multi-Criteria Group Decision Making

Agbodah

Darko

2019

Symmetry

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One of the major problems of varied knowledge-based systems has to do with aggregation and fusion. Pang’s probabilistic linguistic term sets denotes aggregation of fuzzy information and it has attracted tremendous interest from researchers recently. The purpose of this article is to deal investigating methods of information aggregation under the probabilistic linguistic environment. In this situation we defined certain Einstein operational laws on probabilistic linguistic term elements (PLTESs) based on Einstein product and Einstein sum. Consequently, we develop some probabilistic linguistic aggregation operators, notably the probabilistic linguistic Einstein average (PLEA) operators, probabilistic linguistic Einstein geometric (PLEG) operators, weighted probabilistic linguistic Einstein average (WPLEA) operators, weighted probabilistic linguistic Einstein geometric (WPLEG) operators. These operators extend the weighted averaging operator and the weighted geometric operator for the purpose of aggregating probabilistic linguistic terms values respectively. Einstein t-norm and Einstein t-conorm constitute effective aggregation tools and they allow input arguments to reinforce each other downwardly and upwardly respectively. We then generate various properties of these operators. With the aid of the WPLEA and WPLEG, we originate the approaches for the application of multiple attribute group decision making (MAGDM) with the probabilistic linguistic term sets (PLTSs). Lastly, we apply an illustrative example to elucidate our proposed methods and also validate their potentials.

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“…Scholars from different fields conducted many important studies, making the extant results fruitful. For example, a theory combining hesitance with the well‐known fuzzy sets theory was recently developed along with a new extension of fuzzy sets called hesitant fuzzy sets; this theory and related applications have been further developed . However, some parts of hesitance phenomena deserve further study because hesitance is a very significant human behavior but is subtle, complex, abstruse, and paradoxical.…”

Section: Introductionmentioning

confidence: 99%

“…For example, a theory combining hesitance with the well-known fuzzy sets theory was recently developed along with a new extension of fuzzy sets called hesitant fuzzy sets 1 ; this theory and related applications have been further developed. [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] However, some parts of hesitance phenomena deserve further study because hesitance is a very significant human behavior but is subtle, complex, abstruse, and paradoxical. Actually, hesitance can also be regarded as a type of uncertainty phenomenon, [21][22][23][24] and one may recall from Atanassov's intuitionistic fuzzy set theory [25][26][27] that the uncertainty, from a special aspect, is embodied by a closed interval [a, b] of [0, 1] with b a π − = representing the uncertainty or hesitance degree.…”

Section: Introductionmentioning

confidence: 99%

Eliciting and measuring hesitance in decision‐making

Jin

2019

Int J Intell Syst

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Hesitance is an innate human psychological phenomenon pervasive in our daily life. Although it is very complex and still not fully understood, there have been many studies related to this interesting topic. In this study, we proposed two fundamental problems about hesitance: the first is the generating problem, which is related to how to elicit hesitance information from human thinking; the second is the measuring problem, which is related to how to devise effective and reasonable methods to measure hesitance degrees from given hesitance information. With these two fundamental questions, we first discussed and analyzed several examples in real life involving hesitance, showing that it can indeed be recorded and represented. Then we roughly classified the hesitance information into two major classes: static hesitance and dynamic hesitance. Some simple and interesting methods were proposed to elicit hesitance, and more reasonable methods were proposed to measure the hesitance degree from the two classes of hesitance information. All methods that have been discussed in this study try to avoid complexity in every aspect while reserving strictness and reasonability; therefore, the present study provides suitable information for practitioners with different backgrounds.

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Entropy of interval-valued intuitionistic hesitant fuzzy set and its application to group decision making problems

Cited by 31 publications

References 58 publications

A Revised Grey Relational Analysis Method for Multicriteria Group Decision-Making with Expected Utility Theory for Oil Spill Emergency Management

A Revised Grey Relational Analysis Method for Multicriteria Group Decision-Making with Expected Utility Theory for Oil Spill Emergency Management

Probabilistic Linguistic Aggregation Operators Based on Einstein t-Norm and t-Conorm and Their Application in Multi-Criteria Group Decision Making

Eliciting and measuring hesitance in decision‐making

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