Hierarchical Punishment-Driven Consensus Model for Probabilistic Linguistic Large-Group Decision Making with Application to Global Supplier Selection

2020 ◽  
Author(s):  
Sumin Yu ◽  
Zhijiao Du ◽  
Xuanhua Xu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Consensus Model ◽  
Large Group ◽  
Global Supplier

Optimization-Based Consensus Model to Solve Multi-Criteria Large Group Decision Making Problems

2020 ◽  
Vol 22 (02) ◽  
pp. 2040010
Author(s):  
Anjali Singh ◽  
Anjana Gupta
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Optimization Theory ◽  
Feedback Mechanism ◽  
Management Decision ◽  
Consensus Model ◽  
Suggested Approach ◽  
Large Group ◽  
Time Problem

In this contribution, a consensus model is proposed to acquire a unified and converging solution of multi-criteria large group decision making problems. Unlike the iterative process and feedback mechanism based models, the suggested approach features the optimization theory to establish the consensus in one go only among the efficient experts. The time salvation characteristic of the model makes it expedient for the emergency planning and management decision problems. The algorithm is validated using the hurricane evacuation notification time problem of United States.

scholarly journals Group Decision-Making Method Based on Expert Classification Consensus Information Integration

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1180
Author(s):  
Lei Wang ◽  
Huifeng Xue
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Clustering Algorithm ◽  
Group Decision ◽  
Final Decision ◽  
Urban Water ◽  
Consensus Model ◽  
Group Consensus ◽  
Large Group ◽  
Consensus Information

Existing decision-making methods are mostly a simple aggregation of expert decision information when solving large group decision-making problems. In these methods, priority should be given to expert weight information; however, it is difficult to avoid the loss of expert decision information in the decision-making process. Therefore, a new idea to solve the problem of large group decision-making by combining the expert group clustering algorithm and the group consensus model is proposed in this paper in order to avoid the disadvantages of subjectively assigning expert weights. First, expert groups are classified by the clustering algorithm of breadth-first search neighbors. Next, the decision information of the experts in the class is corrected adaptively using the group consensus model; then, expert decision information in the class is integrated using probabilistic linguistic translation methods. This method not only avoids the shortcomings of artificially given expert weights, but also reduces the loss of expert decision information. Finally, the method comprehensively considers the scale of the expert class and the difference between the classes to determine the weight of the expert class, and then it weights and integrates the consensus information of all expert classes to obtain the final decision result. This article verifies the effectiveness of the proposed method through a case analysis of urban water resource sustainability evaluation, and provides a scientific evaluation method for the sustainable development level of urban water resources.

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.

A cyclic dynamic trust-based consensus model for large-scale group decision making with probabilistic linguistic information

2021 ◽  
Vol 100 ◽  
pp. 106937
Author(s):  
Xiao Tan ◽  
Jianjun Zhu ◽  
Francisco Javier Cabrerizo ◽  
Enrique Herrera-Viedma
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Large Scale ◽  
Group Decision ◽  
Consensus Model ◽  
Linguistic Information ◽  
Dynamic Trust ◽  
Cyclic Dynamic
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