scholarly journals A 2-dimensional uncertain linguistic MABAC method for multiattribute group decision-making problems

2021 ◽  
Author(s):  
Peide Liu ◽  
Dongyang Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Weighted Average ◽  
Decision Makers ◽  
Maximum Deviation ◽  
Subjective Assessments ◽  
Practical Tool ◽  
Deviation Method

AbstractThe 2-dimensional uncertain linguistic variable (2DULV) can depict decision-makers’ subjective assessments on the reliability of given evaluation results, which is a valid and practical tool to express decision information. In this study, we develop an improved MABAC method with 2DULVs to handle multiattribute group decision-making (MAGDM) problems where the weight information of attributes is unknown. First, some related theories of 2DULVs and the basic procedure of the MABAC method are briefly reviewed. Then, the maximum comprehensive evaluation value method is extended to 2DULVs to obtain combination weights of attributes, in which the subjective weights are determined according to the best–worst method (BWM) and the objective weights are calculated by the maximum deviation method. Besides, the generalized weighted average operator for 2DULVs (2DULGWA) is utilized to aggregate the evaluation information given by all experts. Finally, an improved MABAC for 2DULVs (2DUL-MABAC) is proposed, and an example is carried out to explain the validity of the proposed approach.

scholarly journals TOPSIS Hybrid Multiattribute Group Decision-Making Based on Interval Pythagorean Fuzzy Numbers

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
H. U. Jun ◽  
W. U. Junmin ◽  
W. U. Jie
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Weighted Average ◽  
Decision Makers ◽  
Relative Closeness ◽  
Order Preference ◽  
Pythagorean Fuzzy Numbers

Aiming at the mixed multiattribute group decision-making problem of interval Pythagorean fuzzy numbers, a weighted average (WA) operator model based on interval Pythagorean fuzzy sets is constructed. Furthermore, a decision-making method based on the technique for order preference by similarity to ideal solution (TOPSIS) method with interval Pythagorean fuzzy numbers is proposed. First, based on the completely unknown weights of decision-makers and attributes, interval Pythagorean fuzzy numbers are applied to TOPSIS group decision-making. Second, the interval Pythagorean fuzzy number WA operator is used to synthesize the evaluation matrices of multiple decision-makers into a comprehensive evaluation matrix, and the relative closeness of each scheme is calculated based on the TOPSIS decision-making method. Finally, an example is given to illustrate the rationality and effectiveness of the proposed method.

scholarly journals INTUITIONISTIC FUZZY PRIORITIZED OPERATORS AND THEIR APPLICATION IN MULTI-CRITERIA GROUP DECISION MAKING

2013 ◽  
Vol 19 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Dejian Yu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Weighted Average ◽  
Decision Makers ◽  
Priority Level ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Real Group

Intuitionistic fuzzy set is a very useful tool to depict uncertainty. Lots of multi-criteria group decision making methods under intuitionistic fuzzy environment have been developed. Current methods are under the assumption that the criteria and the decision makers are at the same priority level. However, in real group decision making problems, criteria and decision makers have different priority level commonly. In this paper, multi-criteria group decision making problems where there exists a prioritization relationship over the criteria and decision makers are studied. First, the intuitionistic fuzzy prioritized weighted average (IFPWA) and the intuitionistic fuzzy prioritized weighted geometric (IFPWG) operators are proposed. Then, some of their desirable properties are investigated in detail. Furthermore, the procedure of multi-criteria group decision making based on the proposed operators is given under intuitionistic fuzzy environment. Finally, a practical example about talent introduction is provided to illustrate the developed method.

Visualization of preference aggregation based on Weber point in social network group decision-making problem

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhiqin Yang ◽  
Wuyong Qian ◽  
Jue Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Decision Makers ◽  
Preference Aggregation ◽  
Group Preference ◽  
Content Type ◽  
Trust Propagation ◽  
Decision Making Problem

PurposeThis study aims to construct a Weber point-based model to complete the visualization of preference aggregation in group decision-making problem, in which decision-makers are associated with trust relationship.Design/methodology/approachThis study mainly comprises four parts: trust propagation, preference aggregation, opinion adjustment and alternative selection. Firstly, the incomplete trust between decision-makers is completed with trust transfer operators and propagation probability in trust propagation process. Secondly, a preference aggregation model based on Weber point is proposed to aggregate the group preference visually. Thirdly, opinions are adjusted to reach a consensus. Finally, the ranking of alternatives is determined by the correlation coefficient with the group preference as a reference.FindingsThe Weber point-based model proposed in this study can minimize the gap in the preference of alternatives between the group and all decision-makers, and realize the visualization of aggregation result. A case of plan selection is introduced to illustrate the feasibility and effectiveness of the proposed model.Originality/valueBy comparing the result with the weighted average-based preference aggregation method, the Weber point-based model proposed in this study can show the result of preference aggregation intuitively and improve group consensus.

scholarly journals Pythagorean 2-Tuple Linguistic Taxonomy Method for Supplier Selection in Medical Instrument Industries

2019 ◽  
Vol 16 (23) ◽  
pp. 4875 ◽  
Author(s):  
He ◽  
Wei ◽  
Lu ◽  
Wei ◽  
Lin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Medical Instrument ◽  
Weighted Average ◽  
Decision Makers ◽  
The Novel ◽  
Fuzzy Information ◽  
Multiple Attribute

Supplier selection in medical instrument industries is a classical multiple attribute group decision making (MAGDM) problem. The Pythagorean 2-tuple linguistic sets (P2TLSs) can reflect uncertain or fuzzy information well and solve the supplier selection in medical instrument industries, and the original Taxonomy is very appropriate for comparing different alternatives with respect to their advantages from studied attributes. In this study, we present an algorithm that combines Pythagorean 2-tuple linguistic numbers (P2TLNs) with the Taxonomy method, where P2TLNs are applied to express the evaluation of decision makers on alternatives. Relying on the Pythagorean 2-tuple linguistic weighted average (P2TLWA) operator or Pythagorean 2-tuple linguistic weighted geometric (P2TLWG) operator to fuse P2TLNs, the new general framework is established for Pythagorean 2-tuple linguistic multiple attribute group decision making (MAGDM) under the classical Taxonomy method. Ultimately, an application case for supplier selection in medical instrument industries is designed to test the novel method’s applicability and practicality and a comparative analysis with three other methods is used to elaborate further.

scholarly journals Multistage Multiattribute Group Decision-Making Method Based on Triangular Fuzzy MULTIMOORA

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Wen-feng Dai ◽  
Qiu-yan Zhong ◽  
Chun-ze Qi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Reference Point ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Maximum Deviation ◽  
Triangular Fuzzy Numbers ◽  
System Method ◽  
Multiplicative Form ◽  
Deviation Method

This paper proposed a new multiattribute group decision-making method, in which the period significance coefficients and the attribute significance coefficients are completely unknown, and the attribute values are triangular fuzzy numbers. At first, to obtain the period significance coefficients, the period significance coefficients optimization model is constructed according to the time degree and the differences of the decision information in different periods. Then, attribute significance coefficients are determined by the maximum deviation method. Based on this, alternatives are ranked by the triangular fuzzy ratio system method, the triangular fuzzy reference point method, and the triangular fuzzy full multiplicative form, respectively. The dominance theory is used for aggregating the subordinate rankings into the final ranking. Finally, a numerical example is presented to illustrate the feasibility and effectiveness of the proposed method.

scholarly journals Algorithm for Neutrosophic Soft Sets in Stochastic Multi-Criteria Group Decision Making Based on Prospect Theory

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1085 ◽  
Author(s):  
Dong ◽  
Hou ◽  
Gong
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Decision Makers ◽  
Aggregation Rule ◽  
Decision Matrix ◽  
Soft Sets

To address issues involving inconsistencies, this paper proposes a stochastic multi-criteria group decision making algorithm based on neutrosophic soft sets, which includes a pair of asymmetric functions: Truth-membership and false-membership, and an indeterminacy-membership function. For integrating an inherent stochastic, the algorithm expresses the weights of decision makers and parameter subjective weights by neutrosophic numbers instead of determinate values. Additionally, the algorithm is guided by the prospect theory, which incorporates psychological expectations of decision makers into decision making. To construct the prospect decision matrix, this research establishes a conflict degree measure of neutrosophic numbers and improves it to accommodate the stochastic multi-criteria group decision making. Moreover, we introduce the weighted average aggregation rule and weighted geometric aggregation rule of neutrosophic soft sets. Later, this study presents an algorithm for neutrosophic soft sets in the stochastic multi-criteria group decision making based on the prospect theory. Finally, we perform an illustrative example and a comparative analysis to prove the effectiveness and feasibility of the proposed algorithm.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

scholarly journals A Novel Multi-Criteria Group Decision-Making Approach Based on Bonferroni and Heronian Mean Operators under Hesitant 2-Tuple Linguistic Environment

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1489
Author(s):  
Shahzad Faizi ◽  
Wojciech Sałabun ◽  
Nisbha Shaheen ◽  
Atiq ur Rehman ◽  
Jarosław Wątróbski
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Geometric Bonferroni Mean ◽  
The Individual ◽  
Heronian Mean

Ambiguous and uncertain facts can be handled using a hesitant 2-tuple linguistic set (H2TLS), an important expansion of the 2-tuple linguistic set. The vagueness and uncertainty of data can be grabbed by using aggregation operators. Therefore, aggregation operators play an important role in computational processes to merge the information provided by decision makers (DMs). Furthermore, the aggregation operator is a potential mechanism for merging multisource data which is synonymous with cooperative preference. The aggregation operators need to be studied and analyzed from various perspectives to represent complex choice situations more readily and capture the diverse experiences of DMs. In this manuscript, we propose some valuable operational laws for H2TLS. These new operational laws work through the individual aggregation of linguistic words and the collection of translation parameters. We introduced a hesitant 2-tuple linguistic weighted average (H2TLWA) operator to solve multi-criteria group decision-making (MCGDM) problems. We also define hesitant 2-tuple linguistic Bonferroni mean (H2TLBM) operator, hesitant 2-tuple linguistic geometric Bonferroni mean (H2TLGBM) operator, hesitant 2-tuple linguistic Heronian mean (H2TLHM) operator, and a hesitant 2-tuple linguistic geometric Heronian mean (H2TLGHM) operator based on the novel operational laws proposed in this paper. We define the aggregation operators for addition, subtraction, multiplication, division, scalar multiplication, power and complement with their respective properties. An application example and comparison analysis were examined to show the usefulness and practicality of the work.

Method for Selecting Storage Enterprises Based on IFHA

2015 ◽  
Vol 713-715 ◽  
pp. 1769-1772
Author(s):  
Jie Wu ◽  
Lei Na Zheng ◽  
Tie Jun Pan
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Decision Problems ◽  
Decision Making Process ◽  
Final Decision ◽  
Multiple Decision Makers ◽  
Intuitionistic Fuzzy ◽  
Averaging Operator

In order to reflect the decision-making more scientific and democratic, modern decision problems often require the participation of multiple decision makers. In group decision making process,require the use of intuitionistic fuzzy hybrid averaging operator (IFHA) to get the final decision result.

scholarly journals Some q-Rung Dual Hesitant Fuzzy Heronian Mean Operators with Their Application to Multiple Attribute Group Decision-Making

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 472 ◽  
Author(s):  
Yuan Xu ◽  
Xiaopu Shang ◽  
Jun Wang ◽  
Wen Wu ◽  
Huiqun Huang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Hesitant Fuzzy Sets ◽  
Multiple Attribute ◽  
A New Technique ◽  
Supplier Selection Problem ◽  
Heronian Mean

The q-rung orthopair fuzzy sets (q-ROFSs), originated by Yager, are good tools to describe fuzziness in human cognitive processes. The basic elements of q-ROFSs are q-rung orthopair fuzzy numbers (q-ROFNs), which are constructed by membership and nonmembership degrees. As realistic decision-making is very complicated, decision makers (DMs) may be hesitant among several values when determining membership and nonmembership degrees. By incorporating dual hesitant fuzzy sets (DHFSs) into q-ROFSs, we propose a new technique to deal with uncertainty, called q-rung dual hesitant fuzzy sets (q-RDHFSs). Subsequently, we propose a family of q-rung dual hesitant fuzzy Heronian mean operators for q-RDHFSs. Further, the newly developed aggregation operators are utilized in multiple attribute group decision-making (MAGDM). We used the proposed method to solve a most suitable supplier selection problem to demonstrate its effectiveness and usefulness. The merits and advantages of the proposed method are highlighted via comparison with existing MAGDM methods. The main contribution of this paper is that a new method for MAGDM is proposed.

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