Multiple Attribute Decision Making Based on Hesitant Fuzzy Einstein Geometric Aggregation Operators

Zhou, Xiaoqiang; Li, Qingguo

doi:10.1155/2014/745617

Cited by 10 publications

(11 citation statements)

References 51 publications

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“…Xu and Xia 47 rank the projects according to a direct appeal to distances. Finally, Zhou and Li 54 design a lexicographic ranking that refines the Xia and Xu proposal 44 . A summary of these studies related to HFSs/HFEs ranking is given in Table 1.…”

Section: Our Assumptions and Research Objectivesmentioning

confidence: 99%

“…Obviously, for any choice of the averaging aggregator a concrete ranking of projects arises. 44 Aggregating operators and score functions Farhadinia 15 Xu and Xia 47 Distances and similarities Zhou and Li 54 Lexicographic procedure…”

Section: Our Assumptions and Research Objectivesmentioning

confidence: 99%

“…Within the extended field of Hesitant Fuzzy Sets, which allows for cases with several degrees of membership, there are many application papers that contribute to Multicriteria Decision Making Theory 1,22,44,48,52,51,54 . Multiexpert multicriteria decision making under this requirement has been explored by Xia et al 45 .…”

Section: Literature Review: Project Evaluation Problemsmentioning

confidence: 99%

“…Xu and Xia 47 proceed in a more direct way: they rank the projects according to their distance to the ideal HFS. Finally, Zhou and Li 54 do not produce evaluations of projects but give a lexicographic ranking that refines the proposal 44 .…”

Section: Analysis Of the Problem: The Segment Approachmentioning

confidence: 99%

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A segment-based approach to the analysis of project evaluation problems by hesitant fuzzy sets

Alcantud¹,

Calle²

2016

IJCIS

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We provide a methodology to perform an extensive and systematized analysis of problems where experts voice their opinions on the attributes of projects through a hesitant fuzzy decision matrix. This provides the decision-maker with ample information on which he or she can rely in order to make the final decision, in the form of segments instead of numbers. These segments derive from weighted average of new parametric expressions for two tenable indices of satisfaction, the distance to an ideal or the similarity to an anti-ideal, and permit to give a profuse unified picture of the relative performance of the projects. When the parameter grows, these indices tend to replicate the evaluation by respective simplistic expressions that only depend on the least, resp., the largest, evaluation and the number of evaluations in each cell.

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Section: Our Assumptions and Research Objectivesmentioning

confidence: 99%

Section: Our Assumptions and Research Objectivesmentioning

confidence: 99%

Section: Literature Review: Project Evaluation Problemsmentioning

confidence: 99%

Section: Analysis Of the Problem: The Segment Approachmentioning

confidence: 99%

See 2 more Smart Citations

A segment-based approach to the analysis of project evaluation problems by hesitant fuzzy sets

Alcantud¹,

Calle²

2016

IJCIS

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“…In the recent authoritative survey of HFSs [9], the authors summarize many useful and valuable decision making methods to solve hesitant fuzzy multicriteria decision making problems and propose further applications of HFSs to decision making. Within the extended field of Hesitancy in Fuzzy Sets, application papers that contribute to multicriteria decision making include [7], [10], [11], [12], [13], [14], [15] and [16]. Multiexpert multicriteria decision making under this requirement has been explored by Xia et al [17] or Tan et al [18] among others.…”

Section: Introductionmentioning

confidence: 99%

Hesitant Fuzzy Worth: An innovative ranking methodology for hesitant fuzzy subsets

Alcantud

Calle

Torrecillas

2016

Applied Soft Computing

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We introduce a novel methodology for ranking hesitant fuzzy sets. It builds on a recent, theoretically sound contribution in Social Choice. In order to justify the applicability of such analysis, we develop two real implementations: (i) new metarankings of world academic institutions that build on real data from three reputed agencies, and (ii) a new procedure for improving teaching performance assessments which we illustrate with real data collected by ourselves. These applications provide new grounds for the theoretical model by hesitant fuzzy sets.

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On Typical Hesitant Fuzzy Prioritized “or” Operator in Multi-Attribute Decision Making

Zhao

2015

Int. J. Intell. Syst.

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Since hesitant fuzzy set was proposed, multi‐attribute decision making (MADM) with hesitant fuzzy information, which is also called hesitant fuzzy MADM, has been a hot research topic in decision theory. This paper investigates a special kind of hesitant fuzzy MADM problems in which the decision data are expressed by several possible values, and the evaluative attributes are in different priority levels. Firstly, we introduce the definitions of hesitant fuzzy t‐norm and t‐conorm by extending the notions of t‐norm and t‐conorm to the hesitant fuzzy environment and explore their constructions by means of t‐norms and t‐conorms. Then motivated by the prioritized “or” operator (R. R. Yager, Prioritized aggregation operators, International Journal of Approximate Reasoning 2008;48:263–274), we develop the typical hesitant fuzzy prioritized “or” operator based on the developed hesitant fuzzy t‐norms and t‐conorms. In this operator, the degree of satisfaction of each alternative in each priority level is derived from a hesitant fuzzy t‐conorm to preserve trade‐offs among the attributes in the same priority level, and the priority weights of attributes are induced by a hesitant fuzzy t‐norm to model the prioritization relationship among attributes. Furthermore, we apply the developed typical hesitant fuzzy prioritized “or” operator to solving the MADM problems in which the decision data are expressed by several possible values and the attributes are in different priority levels. In addition, two numerical examples are given to, respectively, illustrate the applicability and superiority of the developed aggregation operator by comparative analyses with previous research.

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Multiple Attribute Decision Making Based on Hesitant Fuzzy Einstein Geometric Aggregation Operators

Cited by 10 publications

References 51 publications

A segment-based approach to the analysis of project evaluation problems by hesitant fuzzy sets

A segment-based approach to the analysis of project evaluation problems by hesitant fuzzy sets

Hesitant Fuzzy Worth: An innovative ranking methodology for hesitant fuzzy subsets

On Typical Hesitant Fuzzy Prioritized “or” Operator in Multi-Attribute Decision Making

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