Generalized Fuzzy Additive Operators on Intuitionistic Fuzzy Sets and Interval-Valued Intuitionistic Fuzzy Sets and Their Application

Zhang, Fangwei; Huang, Weiwei; Ji, Sun; Liu, Z. D.; Zhu, Yangyong; Li, K. T.; Xu, Shihe; Li, Qiang

doi:10.1109/access.2019.2906945

Cited by 9 publications

(4 citation statements)

References 36 publications

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“…Sometimes, real numbers that are used to express membership and nonmembership are very difficult. Therefore, Atanassov proposed the concept of interval-valued intuitionistic fuzzy set (iIFS); that is, rather than real numbers, in his research work, the membership and nonmembership degrees are represented by interval numbers [ 11 ]. Compared with IFNs, interval-valued intuitionistic fuzzy numbers (iIFNs) can better deal with the uncertainty of decision-making information and ambiguity.…”

Section: Introductionmentioning

confidence: 99%

Entropy-Based Fuzzy TOPSIS Method for Investment Decision Optimization of Large-Scale Projects

Cao

2022

Computational Intelligence and Neuroscience

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Investment of large-scale projects must consider various factors, such as economic conditions and investment environment when making decisions. In large-scale project investment problems, almost 90% of them are completed in a multiobjective context. To this end, the authors of this paper have proposed an entropy-based fuzzy TOPSIS synthesis method to assist in the decision-making optimization of large-scale project investment. Firstly, in accordance with the background of the development of multiattribute decision-making method (MADM), closely related to large-scale project investment, the related research works were studied, and the relevant methods are sorted out. Then, the improved vague-entropy-weight based fuzzy TOPSIS (VEWF-TOPSIS) method, entropy and interval language intuitionistic fuzzy sets based TOPSIS (EILIF-TOPSIS) method, and information entropy attribute importance based intuitionistic fuzzy TOPSIS (IEAI-IF-TOPSIS) method were introduced, and a synthesis MADM method that comprehensively combines the above three methods was proposed. Finally, a numerical case was constructed to properly show the effectiveness of the method proposed in the present work, and the conclusions were put forward for providing ideas and methods for large-scale project investment decision-making. It is of great significance that the proposed framework would make large-scale project investment decisions more reasonable and practical, which enriches the research methods of MADM problems to a certain extent and can provide reference for the actual large-scale project investment decision-making problems.

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Section: Introductionmentioning

confidence: 99%

Entropy-Based Fuzzy TOPSIS Method for Investment Decision Optimization of Large-Scale Projects

Cao

2022

Computational Intelligence and Neuroscience

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“…Due to such capability, IFSs have been widely applied to describe attribute values in MADM. Various research topics regarding IFSs in MADM, such as calculus for IFSs Xu 2016, 2017;Ai and Xu 2018), intuitionistic preference relations (Liao and Xu 2014;Liao et al 2015;Pedrycz 2017a, 2018;Zhang et al 2020), operations for IFSs (Jamkhaneh and Garg 2018;Dutta 2019;Dutta and Saikia 2019), information measures for IFSs (Chen et al 2016a;Kumar 2018, 2019;Song et al 2019;Tan et al 2020), aggregation operators (AOs) of intuitionistic fuzzy numbers (IFNs) for MADM (Xu and Yager 2011;Chen and Chang 2016;Liu and Chen 2017;Liu and Tang 2018;Zhang et al 2019;Seikh and Mandal 2019;Liu et al 2020), and MADM methods based on IFSs (Wang and Zhang 2013;Chen et al 2016b;Garg 2017a;Zhang and Pedrycz 2017b;Kumar and Garg 2018;Rani et al 2019;Zeng et al 2019), have received widespread attention.…”

Section: Introductionmentioning

confidence: 99%

Multiple-attribute decision-making based on picture fuzzy Archimedean power Maclaurin symmetric mean operators

et al. 2020

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In this paper, a novel multiple attribute decision making method based on a set of Archimedean power Maclaurin symmetric mean operators of picture fuzzy numbers is proposed. The Maclaurin symmetric mean operator, power average operator, and operational rules based on Archimedean T-norm and T-conorm are introduced into picture fuzzy environment to construct the aggregation operators. The formal definitions of the aggregation operators are presented. Their general and specific expressions are established. The properties and special cases of the aggregation operators are respectively explored and discussed. Using the presented aggregation operators, a method for solving the multiple attribute decision making problems based on picture fuzzy numbers is designed. The method is illustrated through example and experiments and validated by comparisons. The results of the comparisons show that the proposed method is feasible and effective that can provide the generality and flexibility in aggregation of values of attributes and consideration of interactions among attributes and the capability to lower the negative effect of biased attribute values on the result of aggregation.

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“…Compared with FSs, IFSs provide more sufficient decision information and more effectively handle DMs' uncertain evaluation values. Therefore, IFSs based on MADM has soon become a new research topic and many decision-making methods have been proposed [12]- [16].…”

Section: Introductionmentioning

confidence: 99%

Multi-Attribute Decision-Making Based on Interval-Valued q-Rung Dual Hesitant Uncertain Linguistic Sets

Shang

Wang

et al. 2020

IEEE Access

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The interval-valued q-rung dual hesitant fuzzy sets (IVq-RDHFSs) effectively model decision makers' (DMs') evaluation information as well as their high hesitancy in complicated multi-attribute decision-making (MADM) situations. Note that the IVq-RDHFSs only depict DMs' evaluation values quantificationally but overlook their qualitative decision information. To improve the performance of IVq-RDHFSs in dealing with fuzzy information, we incorporate the concept of uncertain linguistic variables (ULVs) into them and propose a new tool, called interval-valued q-rung dual hesitant uncertain linguistic sets (IVq-RDHULSs). Then we investigate MADM approach with interval-valued q-rung dual hesitant uncertain linguistic (IVq-RDHUL) information. Afterwards, the concept of IVq-RDHULSs as well as their operations and ranking method are proposed. Further, we propose a set of IVq-RDHUL aggregation operators (AOs) on the basis of the powerful Muirhead mean, i.e., the IVq-RDHUL Muirhead mean operator, the IVq-RDHUL weighted Muirhead mean operator, the IVq-RDHUL dual Muirhead mean operator, and the IVq-RDHUL weighted dual Muirhead mean operator. The significant properties of the proposed AOs are also discussed in detail. Lastly, we try to introduce a new method to MADM issues in IVq-RDHUL context based on the newly developed AOs. INDEX TERMS Interval-valued q-rung dual hesitant fuzzy sets, interval-valued q-rung dual hesitant uncertain linguistic sets, Muirhead mean, multi-attribute decision-making.

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Generalized Fuzzy Additive Operators on Intuitionistic Fuzzy Sets and Interval-Valued Intuitionistic Fuzzy Sets and Their Application

Cited by 9 publications

References 36 publications

Entropy-Based Fuzzy TOPSIS Method for Investment Decision Optimization of Large-Scale Projects

Entropy-Based Fuzzy TOPSIS Method for Investment Decision Optimization of Large-Scale Projects

Multiple-attribute decision-making based on picture fuzzy Archimedean power Maclaurin symmetric mean operators

Multi-Attribute Decision-Making Based on Interval-Valued q-Rung Dual Hesitant Uncertain Linguistic Sets

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