scholarly journals Spherical Fuzzy Logarithmic Aggregation Operators Based on Entropy and Their Application in Decision Support Systems

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 628 ◽  
Author(s):  
Yun Jin ◽  
Shahzaib Ashraf ◽  
Saleem Abdullah
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision ◽  
Weighted Average ◽  
Fuzzy Decision Making ◽  
Practical Case ◽  
Fuzzy Decision ◽  
Comparison Analysis ◽  
Fuzzy Weighted Average ◽  
Novel Method

Keeping in view the importance of new defined and well growing spherical fuzzy sets, in this study, we proposed a novel method to handle the spherical fuzzy multi-criteria group decision-making (MCGDM) problems. Firstly, we presented some novel logarithmic operations of spherical fuzzy sets (SFSs). Then, we proposed series of novel logarithmic operators, namely spherical fuzzy weighted average operators and spherical fuzzy weighted geometric operators. We proposed the spherical fuzzy entropy to find the unknown weights information of the criteria. We study some of its desirable properties such as idempotency, boundary and monotonicity in detail. Finally, the detailed steps for the spherical fuzzy decision-making problems were developed, and a practical case was given to check the created approach and to illustrate its validity and superiority. Besides this, a systematic comparison analysis with other existent methods is conducted to reveal the advantages of our proposed method. Results indicate that the proposed method is suitable and effective for the decision process to evaluate their best alternative.

INTUITIONISTIC FUZZY DECISION-MAKING WITH SIMILARITY MEASURES AND OWA OPERATOR

2013 ◽  
Vol 21 (02) ◽  
pp. 245-262 ◽  
Author(s):  
WEIHUA SU ◽  
YONG YANG ◽  
CHONGHUI ZHANG ◽  
SHOUZHEN ZENG
Keyword(s):  
Decision Making ◽  
Similarity Measures ◽  
Weighted Average ◽  
Fuzzy Decision Making ◽  
Practical Case ◽  
Owa Operator ◽  
Fuzzy Decision ◽  
Consensus Analysis ◽  
Intuitionistic Fuzzy ◽  
Wide Range

In this paper, we present a new intuitionistic fuzzy decision-making technique based on similarity measures and the ordered weighted average (OWA) operator. We develop the intuitionistic fuzzy ordered weighted similarity (IFOWS) measure. The main advantage of the IFOWS measure is that it can alleviate the influence of unduly large (or small) deviations on the aggregation results by assigning them low (or high) weights. Moreover, it provides a very general formulation that includes a wide range of aggregation similarity measures and aggregates the input arguments taking the form of intuitionistic fuzzy values rather than exact numbers. We further develop the interval-valued intuitionistic fuzzy ordered weighted similarity (IVIFOWS) measure. Then we apply the developed similarity measures for consensus analysis in group decision-making with intuitionistic fuzzy information. Finally, a practical case is used to illustrate the developed procedures.

scholarly journals Fuzzy sets and fuzzy decision making in nutrition

1997 ◽  
Vol 51 (5) ◽  
pp. 286-296 ◽  
Author(s):  
B Wirsam ◽  
A Hahn ◽  
EO Uthus ◽  
C Leitzmann
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision

scholarly journals Dual Extended Hesitant Fuzzy Sets

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 714 ◽  
Author(s):  
José Carlos R. Alcantud ◽  
Gustavo Santos-García ◽  
Xindong Peng ◽  
Jianming Zhan
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Natural Extension ◽  
Score Function ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Hesitant Fuzzy Sets ◽  
Weight Score ◽  
Decision Making Problem

Hesitant fuzzy sets extend fuzzy sets by considering many-valued sets of membership degrees. Real applications validate this model and decision making approaches of various forms permit to act in a flexible manner. If we can avail ourselves of hesitant information on non-membership degrees too, then dual hesitant fuzzy sets provide a natural extension of both hesitant fuzzy sets and intuitionistic fuzzy sets. This article defines the concept of dual extended hesitant fuzzy set as the combination of extended hesitant fuzzy sets with dual hesitant fuzzy sets. Its basic algebraic properties are set forth, and the model is linked to other successful models in the literature. We also define a comparison law for the prioritization of elements described in this new framework. Moreover, we present an algorithm to solve the dual extended hesitant fuzzy decision making problem by a weight score function. Finally, the feasibility of this approach is demonstrated by the evaluation of big data industries with an effectiveness test.

scholarly journals Three-Way Decisions with Interval-Valued Intuitionistic Fuzzy Decision-Theoretic Rough Sets in Group Decision-Making

Symmetry ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 281 ◽  
Author(s):  
Dajun Ye ◽  
Decui Liang ◽  
Pei Hu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Rough Sets ◽  
Group Decision ◽  
Intuitionistic Fuzzy Sets ◽  
Fuzzy Decision ◽  
Grey Correlation ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

In this article, we demonstrate how interval-valued intuitionistic fuzzy sets (IVIFSs) can function as extended intuitionistic fuzzy sets (IFSs) using the interval-valued intuitionistic fuzzy numbers (IVIFNs) instead of precision numbers to describe the degree of membership and non-membership, which are more flexible and practical in dealing with ambiguity and uncertainty. By introducing IVIFSs into three-way decisions, we provide a new description of the loss function. Thus, we firstly propose a model of interval-valued intuitionistic fuzzy decision-theoretic rough sets (IVIFDTRSs). According to the basic framework of IVIFDTRSs, we design a strategy to address the IVIFNs and deduce three-way decisions. Then, we successfully extend the results of IVIFDTRSs from single-person decision-making to group decision-making. In this situation, we adopt a grey correlation accurate weighted determining method (GCAWD) to compute the weights of decision-makers, which integrates the advantages of the accurate weighted determining method and grey correlation analysis method. Moreover, we utilize the interval-valued intuitionistic fuzzy weighted averaging (IIFWA) operation to count the aggregated scores and the accuracies of the expected losses. By comparing these scores and accuracies, we design a simple and straightforward algorithm to deduce three-way decisions for group decision-making. Finally, we use an illustrative example to verify our results.

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