Possibility degree and divergence degree based method for interval-valued intuitionistic fuzzy multi-attribute group decision making

Wang, Feng; Wan, Shouhong

doi:10.1016/j.eswa.2019.112929

Cited by 39 publications

(29 citation statements)

References 49 publications

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“…Next, an example from [12], in which the weights of the attribute are known while the weights of the experts are unknown. Based on the aforementioned example, we show the method introduced in Section 4 is effective.…”

Section: Examplementioning

confidence: 99%

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Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment

Li¹,

Cheng²,

Qiong³

et al. 2020

IJCIS

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This paper studies the multi-attribute group decision-making problems with unknown experts' weights under interval-valued intuitionistic fuzzy environment. First, in order to provide more flexibilities for decision-makers in actual decision-making problems, a novel cross-entropy measure with parameter of interval-valued intuitionistic fuzzy set (IVIFS) based on J-divergence is proposed. The novel cross-entropy measure can obtain more flexible and practical optimal ranking results by adjusting the parameter. Then, by using the designed cross-entropy measure, two models are established to obtain experts' weights, which consider the influence of experts' experience and professional knowledge on experts' weights. Finally, two examples are provided to illustrate the effectiveness and applicability of optimizing the group decision-making approach.

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Section: Examplementioning

confidence: 99%

“…Since the membership and nonmembership of IVIF are described by intervals, IVIFS is better than IFS in representing fuzziness and uncertainty [10]. Since its appearance in the literature, the IVIFS and its extension theory has attracted increasing attention, many fuzzy MAGDM approaches have been presented [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment

Li¹,

Cheng²,

Qiong³

et al. 2020

IJCIS

View full text Add to dashboard Cite

show abstract

“…Several approaches have been proposed for deriving the attribute weights: the simple multi-attribute rating technique [53], the judgement pairwise comparison method [54], the fuzzy programming method [55], the information entropy method [56], the maximal deviation-based method [57], and adjusted possibility distribution matrices [58]. 4) Considering = { !…”

Section: Dmagdm Environment Based On Ifs Theorymentioning

confidence: 99%

An Integrated Approach for Fuzzy-Dynamic Multi-Attribute Group Decision Making With Application in Renewable Energy

Almulhim

Barahona

2020

IEEE Access

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This paper proposes a methodology for tackling intuitionistic fuzzy-dynamic multi-attribute group decision-making (IF-DMAGDM) problems in the presence of uncertainty. The ELECTRE I approach is integrated with the VIKOR method by considering intuitionistic fuzzy set environments (IFSs). This work introduces a novel form of representing how informed judgements affect the performance of alternatives with respect to attributes at different times that take the form of IFSs. The proposal incorporates three different relative weights: the first is for the decision makers, the second is for the attributes in each range of time, and the last is for the time intervals themselves. The method is suitable for complex and conflicting scenarios, and how an expert's opinion changes over an interval of time is accurately described. An evaluation of the sustainability indicators for renewable energy systems is provided as an illustrative example. To validate the results, a sensitivity analysis and comparative analysis with existing methods are presented.

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“…The IFS is a new mathematical tool for dealing with uncertain and complex information efficiently, which is widely used in the field of multi-attribute decision-making (MADM) [ 12 , 13 , 14 ]. In recent years, scholars have made great progress in the research of intuitionistic fuzzy multi-attribute decision-making (IFMADM).…”

Section: Introductionmentioning

confidence: 99%

A New Multi-Attribute Emergency Decision-Making Algorithm Based on Intuitionistic Fuzzy Cross-Entropy and Comprehensive Grey Correlation Analysis

et al. 2020

Entropy

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Intuitionistic fuzzy distance measurement is an effective method to study multi-attribute emergency decision-making (MAEDM) problems. Unfortunately, the traditional intuitionistic fuzzy distance measurement method cannot accurately reflect the difference between membership and non-membership data, where it is easy to cause information confusion. Therefore, from the intuitionistic fuzzy number (IFN), this paper constructs a decision-making model based on intuitionistic fuzzy cross-entropy and a comprehensive grey correlation analysis algorithm. For the MAEDM problems of completely unknown and partially known attribute weights, this method establishes a grey correlation analysis algorithm based on the objective evaluation value and subjective preference value of decision makers (DMs), which makes up for the shortcomings of traditional model information loss and greatly improves the accuracy of MAEDM. Finally, taking the Wenchuan Earthquake on May 12th 2008 as a case study, this paper constructs and solves the ranking problem of shelters. Through the sensitivity comparison analysis, when the grey resolution coefficient increases from 0.4 to 1.0, the ranking result of building shelters remains stable. Compared to the traditional intuitionistic fuzzy distance, this method is shown to be more reliable.

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Possibility degree and divergence degree based method for interval-valued intuitionistic fuzzy multi-attribute group decision making

Cited by 39 publications

References 49 publications

Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment

Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment

An Integrated Approach for Fuzzy-Dynamic Multi-Attribute Group Decision Making With Application in Renewable Energy

A New Multi-Attribute Emergency Decision-Making Algorithm Based on Intuitionistic Fuzzy Cross-Entropy and Comprehensive Grey Correlation Analysis

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