scholarly journals Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 37
Author(s):  
Ye Li ◽  
Yisheng Liu
Keyword(s):  
Decision Making ◽  
Qualitative Evaluation ◽  
Multiple Attribute Decision Making ◽  
Two Dimensional ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weight ◽  
Model Based ◽  
Subjective Weight ◽  
Multiple Attribute

Considering the advantages of trapezoid fuzzy two-dimensional linguistic variables (TrF2DLVs), which can not only accurately describe the qualitative evaluation but also use qualitative linguistic variables (LVs) to describe the confidence level of this evaluation in the second dimension, this paper proposes a novel method based on trapezoidal fuzzy two-dimensional linguistic information to solve multiple attribute decision-making (MADM) problems with unknown attribute weight. First, a combination weight model is constructed, which covers a subjective weight determination model based on the proposed trapezoidal fuzzy two-dimensional linguistic best-worst method (TrF2DL-BWM) and an objective weight determination model based on the proposed CRITIC method. Then, in order to accurately rank the alternatives, an extended VIKOR-QUALIFLEX method is proposed, which can measure the concordance index of each ranking combination by means of group utility and individual maximum regret value of each evaluation alternative. Finally, a practical problem of lean management assessment for industrial residential projects is solved by the proposed method, and the effectiveness and advantages of the method are demonstrated by comparative analysis and discussion.

scholarly journals Intuitionistic Linguistic Weighted Bonferroni Mean Operator and Its Application to Multiple Attribute Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Peide Liu ◽  
Lili Rong ◽  
Yanchang Chu ◽  
Yanwei Li
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Linguistic Variables ◽  
Fuzzy Information ◽  
Linguistic Information ◽  
Bonferroni Mean ◽  
Multiple Attribute ◽  
Special Cases ◽  
The Individual

The intuitionistic linguistic variables are easier to describe the fuzzy information which widely exists in the real world, and Bonferroni mean can capture the interrelationship of the individual arguments. However, the traditional Bonferroni mean can only process the crisp number. In this paper, we will extend Bonferroni mean to the intuitionistic linguistic environment and propose a multiple attribute decision making method with intuitionistic linguistic information based on the extended Bonferroni mean which can consider the interrelationship of the attributes. Firstly, score function and accuracy function of intuitionistic linguistic numbers are introduced. Then, an intuitionistic linguistic Bonferroni mean (ILBM) operator and an intuitionistic linguistic weighted Bonferroni mean (ILWBM) operator are developed, and some desirable characteristics of them are studied. At the same time, some special cases with respect to the parameterspandqin Bonferroni are analyzed. Based on the ILWBM operator, the approach to multiple attribute decision making with intuitionistic linguistic information is proposed. Finally, an illustrative example is given to verify the developed approach and to demonstrate its effectiveness.

scholarly journals AN APPROACH TO GROUP DECISION MAKING BASED ON 2-DIMENSION UNCERTAIN LINGUISTIC INFORMATION

2012 ◽  
Vol 18 (3) ◽  
pp. 424-437 ◽  
Author(s):  
Peide Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Multiple Attribute Decision Making ◽  
Maximum Deviation ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Evaluation Information

Based on the definition of 2-dimension linguistic information of multiple attribute decision making problems proposed by Zhu, Zhou and Yang (2009), the information on evaluation is extended to 2-dimension uncertain linguistic variables, and a new method is proposed to solve the multiple-attribute group decision making problems in which the attribute values take the form of 2-dimension uncertain linguistic variables and the attribute weights are unknown. Firstly, the II class of uncertain linguistic information is transformed into the subjective weights of the experts, and then the subjective weights, the similarity degree of experts’ evaluation information and authority weights are aggregated to the comprehensive weights of each expert. By the comprehensive weights, the group decision making matrix is produced by weighting evaluation information of each expert. Then the maximum deviation method is used to calculate the attribute weights and TOPSIS method is proposed to rank the alternatives. Finally, an example is given to illustrate the decision-making steps and the effectiveness of this method.

AN APPROACH TO PURE LINGUISTIC MULTIPLE ATTRIBUTE DECISION MAKING UNDER UNCERTAINTY

2005 ◽  
Vol 04 (02) ◽  
pp. 197-206 ◽  
Author(s):  
ZESHUI XU
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Decision Making Under Uncertainty ◽  
Linguistic Variables ◽  
Linguistic Information ◽  
Attribute Weights ◽  
Operational Laws ◽  
Multiple Attribute

The pure linguistic multiple attribute decision making problems are studied, in which the information about the attribute weights are expressed in the form of linguistic variables or uncertain linguistic variables, and the attribute values take the form of uncertain linguistic variables. The operational laws of uncertain linguistic variables are introduced, and two uncertain linguistic aggregation operators called linguistic weighted aggregation operator and uncertain linguistic weighted aggregation operator are developed based on uncertain linguistic variables and their operational laws. An approach based on the developed operators for pure linguistic multiple attribute decision making under uncertainty is proposed. The prominent characteristic of the proposed approach is that it can compute with uncertain linguistic information directly. Furthermore, the approach is straightforward and does not produce any loss of information. Finally, an illustrative example is given.

scholarly journals Research on the Evaluation Model of Urban Tourism Management Efficiency with Uncertain Linguistic Information

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Song-Mao Wang ◽  
Liang-Yan Fang ◽  
Feng Deng
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Multiple Attribute Decision Making ◽  
Urban Tourism ◽  
Weighted Averaging ◽  
Linguistic Information ◽  
Management Efficiency ◽  
Tourism Management ◽  
Proposed Model ◽  
Multiple Attribute

We investigate the multiple attribute decision making problems for evaluating the urban tourism management efficiency with uncertain linguistic information. We utilize the uncertain linguistic weighted averaging (ULWA) operator to aggregate the uncertain linguistic information corresponding to each alternative and get the overall value of the alternatives and, then rank the alternatives and select the most desirable one(s). Finally, a numerical example for evaluating the urban tourism management efficiency with uncertain linguistic information is used to illustrate the proposed model.

Possibility-Based ELECTRE II Method with Uncertain Linguistic Fuzzy Variables

2017 ◽  
Vol 31 (09) ◽  
pp. 1759016 ◽  
Author(s):  
Lidong Wang ◽  
Binquan Liao ◽  
Xiaodong Liu ◽  
Jingxia Liu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Economic Systems ◽  
Linguistic Variables ◽  
Concordance Index ◽  
Fuzzy Variables ◽  
Numerical Example ◽  
Deviation Index ◽  
Multiple Attribute

Linguistic variables can better approximate the fuzziness of man’s thinking, which are important tools for multiple attribute decision-making problems. This paper establishes the possibility-based ELECTRE II model under the environment of uncertain linguistic fuzzy variables and uncertain weight information. By introducing the degree of possibility to ELECTRE II model, the concordance set, the discordance set and the indifferent set are obtained, respectively. Furthermore, the concordance index is redefined by considering deviation index under the same attribute, by which the strong and weak relationships are constructed, and then the rank of alternatives is obtained. A numerical example about the evaluation of socio-economic systems is employed to illustrate the convenience and applicability of the proposed method.

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