scholarly journals Entropy-Based GLDS Method for Social Capital Selection of a PPP Project with q-Rung Orthopair Fuzzy Information

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 414
Author(s):  
Li Liu ◽  
Jiang Wu ◽  
Guiwu Wei ◽  
Cun Wei ◽  
Jie Wang ◽  
...  
Keyword(s):  
Social Capital ◽  
Group Decision ◽  
Fuzzy Entropy ◽  
Fuzzy Information ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
The Social ◽  
Dominance Score ◽  
Magdm Problems ◽  
Selection Of

The social capital selection of a public–private-partnership (PPP) project could be regarded as a classical multiple attribute group decision-making (MAGDM) issue. In this paper, based on the traditional gained and lost dominance score (GLDS) method, the q-rung orthopair fuzzy entropy-based GLDS method was used to solve MAGDM problems. First, some basic theories related to the q-rung orthopair fuzzy sets (q-ROFSs) are briefly reviewed. Then, to fuse the q-rung orthopair fuzzy information effectively, the q-rung orthopair fuzzy Hamacher weighting average (q-ROFHWA) operator and q-rung orthopair fuzzy Hamacher weighting geometric (q-ROFHWG) operator based on the Hamacher operation laws are proposed. Moreover, to determine the attribute weights, the q-rung orthopair fuzzy entropy (q-ROFE) is proposed and some significant merits of it are discussed. Next, based on the q-ROFHWA operator, q-ROFE, and the traditional GLDS method, a MAGDM model with q-rung orthopair fuzzy information is built. In the end, a numerical example for social capital selection of PPP projects is provided to testify the proposed method and deliver a comparative analysis.

scholarly journals Fuzzy Linguistic Induced Ordered Weighted Averaging Operator and Its Application

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Sidong Xian
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Averaging ◽  
Attribute Weights ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Ordered Weighted Averaging Operator ◽  
Fuzzy Linguistic ◽  
Magdm Problems

With respect to multiple attribute group decision making (MAGDM) problems, in which the attribute weights take the form of real numbers, and the attribute values take the form of fuzzy linguistic scale variables, a decision analysis approach is proposed. In this paper, we develop a new fuzzy linguistic induce OWA (FLIOWA) operator and analyze the properties of it by utilizing some operational laws of fuzzy linguistic scale variables. A method based on the FLIOWA operators for multiple attribute group decision making is presented. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

scholarly journals Power Geometric Operators of Hesitant Multiplicative Fuzzy Numbers and Their Application to Multiple Attribute Group Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Lei Wang ◽  
Mingfang Ni ◽  
Zhanke Yu ◽  
Lei Zhu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Fuzzy Information ◽  
Support Measures ◽  
Aggregation Techniques ◽  
Multiple Attribute ◽  
Wide Range ◽  
Magdm Problems

Multiplicative relations are one of most powerful techniques to express the preferences over alternatives (or criteria). In this paper, we propose a wide range of hesitant multiplicative fuzzy power aggregation geometric operators on multiattribute group decision making (MAGDM) problems for hesitant multiplicative information. In this paper, we first develop some compatibility measures for hesitant multiplicative fuzzy numbers, based on which the corresponding support measures can be obtained. Then we propose several aggregation techniques, and investigate their properties. In the end, we develop two approaches for multiple attribute group decision making with hesitant multiplicative fuzzy information and illustrate a real world example to show the behavior of the proposed operators.

scholarly journals Some Induced Correlated Aggregating Operators with Interval Grey Uncertain Linguistic Information and Their Application to Multiple Attribute Group Decision Making

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Zu-Jun Ma ◽  
Nian Zhang ◽  
Ying Dai
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Choquet Integral ◽  
Linguistic Variables ◽  
Attribute Weights ◽  
Operation Rules ◽  
Multiple Attribute ◽  
Correlation Properties ◽  
Magdm Problems

We propose the interval grey uncertain linguistic correlated ordered arithmetic averaging (IGULCOA) operator and the induced interval grey uncertain linguistic correlated ordered arithmetic averaging (I-IGULCOA) operator based on the correlation properties of the Choquet integral and the interval grey uncertain linguistic variables to investigate the multiple attribute group decision making (MAGDM) problems, in which both the attribute weights and the expert weights are correlative. Firstly, the relative concepts of interval grey uncertain linguistic variables are defined and the operation rules between the two interval grey uncertain linguistic variables are established. Then, two new aggregation operators: the interval grey uncertain linguistic correlated ordered arithmetic averaging (IGULCOA) operator and the induced interval grey uncertain linguistic correlated ordered arithmetic averaging (I-IGULCOA) operator are developed and some desirable properties of the I-IGULCOA operator are studied, such as commutativity, idempotency, monotonicity, and boundness. Furthermore, the IGULCOA and I-IGULCOA operators based approach is developed to solve the MAGDM problems, in which both the attribute weights and the expert weights are correlative and the attribute values take the form of the interval grey uncertain linguistic variables. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

FUZZY POWER AGGREGATION OPERATORS AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING

2013 ◽  
Vol 19 (3) ◽  
pp. 377-396 ◽  
Author(s):  
Guiwu Wei ◽  
Xiaofei Zhao ◽  
Hongjun Wang ◽  
Rui Lin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Magdm Problems ◽  
The Ideal

The article investigates the multiple attribute group decision making (MAGDM) problems in which the attribute values take the form of triangular fuzzy information. Motivated by the ideal of power aggregation, in this paper some power aggregation operators for aggregating triangular fuzzy information are developed and then applied in order to develop some models for multiple attribute group decision making with triangular fuzzy information. Finally, some illustrative examples are given to verify the developed approach and to demonstrate its practicality and effectiveness.

scholarly journals Selecting the Low-Carbon Tourism Destination: Based on Pythagorean Fuzzy Taxonomy Method

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 832 ◽  
Author(s):  
Guiwu Wei ◽  
Yanxin Tang ◽  
Mengwei Zhao ◽  
Rui Lin ◽  
Jiang Wu
Keyword(s):  
Group Decision ◽  
Entropy Method ◽  
Uncertain Information ◽  
Low Carbon ◽  
Fuzzy Information ◽  
Tourist Destination ◽  
Tourist Destinations ◽  
Attribute Weights ◽  
Fuzzy Environment ◽  
Multiple Attribute

Low-carbon tourism plays the increasingly significant role in carbon emission reduction and natural environmental protection. The choice of low-carbon tourist destination (LCTD) often involves the multiple attributes or criteria and can be regarded as the corresponding multiple attribute group decision making (MAGDM) issues. Since the Pythagorean fuzzy sets (PFSs) could well depict uncertain information or fuzzy information and cope with the LCTD selection, thus this essay develops a framework to tackle such MAGDM issues under the Pythagorean fuzzy environment. In this essay, due to few methods can compare with different alternatives along with their advantages from designed attributes, therefore, to overcome this challenge, the taxonomy method is utilized to integrate with PFSs. What’s more, the entropy method is also utilized to determine the attribute weights. Eventually, an application related to LCTD selection and some comparative analysis have been given to demonstrate the superiority of the designed method. The results illustrate that the designed framework is useful for identifying optimal tourist destination among the potential tourist destinations.

scholarly journals AN APPROACH TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING WITH INTERVAL INTUITIONISTIC TRAPEZOIDAL FUZZY INFORMATION

2012 ◽  
Vol 18 (2) ◽  
pp. 317-330 ◽  
Author(s):  
Guiwu Wei ◽  
Xiaofei Zhao ◽  
Hongjun Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Real Numbers ◽  
Trapezoidal Fuzzy Numbers ◽  
Attribute Weights ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Magdm Problems

In this paper, we investigate the multiple attribute group decision making (MAGDM) problems in which both the attribute weights and the expert weights take the form of real numbers, attribute values take the form of interval intuitionistic trapezoidal fuzzy numbers. Firstly, some operational laws of interval intuitionistic trapezoidal fuzzy numbers are introduced. Then some new aggregation operators including interval intuitionistic trapezoidal fuzzy ordered weighted geometric (IITFOWG) operator and interval intuitionistic trapezoidal fuzzy hybrid geometric (IITFHG) operator are proposed and some desirable properties of these operators are studied, such as commutativity, idempotency and monotonicity. An IITFWG and IITFHG operators-based approach is developed to solve the MAGDM problems in which both the attribute weights and the expert weights take the form of real numbers and attribute values take the form of interval intuitionistic trapezoidal fuzzy numbers. Finally, some illustrative examples are given to verify the developed approach and to demonstrate its practicality and effectiveness.

CPT-MABAC-Based multiple attribute group decision making method with probabilistic hesitant fuzzy information

2021 ◽  
pp. 1-16
Author(s):  
Ningna Liao ◽  
Hui Gao ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Fuzzy Information ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
Probabilistic Hesitant Fuzzy Sets ◽  
Magdm Problems

Facing with a sea of fuzzy information, decision makers always feel it difficult to select the optimal alternatives. Probabilistic hesitant fuzzy sets (PHFs) utilize the possible numbers and the possible membership degrees to describe the behavior of the decision makers. though this environment has been introduced to solve problems using different methods, this circumstance can still be explored by using different method. This paper’ s aim is to develop the MABAC (Multi-Attributive Border Approximation area Comparison) decision-making method which based on cumulative prospect theory (CPT) in probabilistic hesitant fuzzy environment to handle multiple attributes group decision making (MAGDM) problems. Then the weighting vector of attributes can be calculated by the method of entropy. Then, in order to show the applicability of the proposed method, it is validated by a case study for buying a house. Finally, through comparing the outcome of comparative analysis, we conclude that this designed method is acceptable.

The Compromise Ratio Method With Intuitionistic Fuzzy Distance for FMAGDM

2022 ◽  
Vol 11 (1) ◽  
pp. 1-17
Author(s):  
Shuai Li ◽  
Jingjing An ◽  
Jiangxia Nan
Keyword(s):  
Distance Measure ◽  
Group Decision ◽  
Ratio Method ◽  
Linguistic Variables ◽  
Software Selection ◽  
Fuzzy Distance ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Magdm Problems

The compromise ratio method (CRM) is an effective method to solve multiple attribute group decision making (MAGDM). Distance measure of intuitionistic fuzzy (IF) numbers (IFNs) is important for CRM. In this paper, according to the IF distance of IFNs, an extended compromise ratio method (CRM) is developed for (MAGDM) problems which attribute weights and evaluation values of alternatives on attributes are expressed in linguistic variables parameterized using TIFNs. Finally, the effectiveness and practicability of the extended CRM with IF distance are demonstrated by solving a software selection problem.

Taxonomy-based multiple attribute group decision making method with probabilistic uncertain linguistic information and its application in supplier selection

2021 ◽  
pp. 1-14
Author(s):  
Yan He ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Medical Instrument ◽  
Uncertain Information ◽  
Suitable Alternative ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Linguistic Term ◽  
Selection Of

The optimal supplier selection in medical instrument industries could be considered a classical MAGDM issue. The probabilistic uncertain linguistic term sets (PULTSs) could depict uncertain information well and the Taxonomy method is appropriate to compare various alternatives according to their merits and utility degree from studied attributes. In such paper, we develop a Taxonomy method for probabilistic uncertain linguistic MAGDM (PUL-MAGDM) with the completely unknown attribute weights. Above all, the score function’s definition is utilized to derive the weights of attribute based upon the CRITIC method. In addition, the probabilistic uncertain linguistic development pattern (PULDP) is improved and the smallest development attribute value from the positive ideal solution under PULTSs is calculated to determine the optimal alternative. In the end, taking the supplier selection in medical instrument industries as an example, we demonstrate the usage of the developed algorithms. Based on this, the comparison of methods is conducted with existing methods, such as PUL-TOPSIS method, the PULWA operator, the PUL-EDAS method and the ULWA operator. The results verify that the decision-making framework is valid and effective for supplier selection. Thus, the advantage of this designed method is that it is simple to understand and easy to compute. The designed method can also contribute to the selection of suitable alternative successfully in other selection issues.

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