Probabilistic Uncertain Linguistic EDAS Method Based on Prospect Theory for Multiple Attribute Group Decision-Making and Its Application to Green Finance

2022 ◽  
Author(s):  
Yong Su ◽  
Mengwei Zhao ◽  
Guiwu Wei ◽  
Cun Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Green Finance ◽  
Multiple Attribute

EDAS method based on cumulative prospect theory for multiple attribute group decision-making under picture fuzzy environment

2021 ◽  
pp. 1-13
Author(s):  
Zhiwei Jiang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Cumulative Prospect Theory ◽  
Shopping Mall ◽  
Corporate Executives ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
New City

For the long-term development of shopping mall, the managers of shopping mall tend to build a new store to expand the enterprise’s market share in a new city. After holding a preliminary survey of the city, managers have initially identified five sites for construction. In order to select an optimal site, managers invite four experts who come from university, marking statistics, corporate executives and accounting to score sites. And they choose the best site on the basis of scores. The trait of EDAS method is to select an optimal alternative by using the distance of each alternative from the first-rank value. In this manuscript, we build the picture fuzzy EDAS method based on the cumulative prospect theory (PF-CPT-EDAS) for multiple attribute group decision-making (MAGDM) and it can help managers to choose an optimal alternative effectively. During the procedure of PF-CPT-EDAS means, we take advantage of the entropy means to calculate the original weights of all attributes. Ultimately, we testify the effectiveness of the novel model by comparing the overcome of PF-CPT-EDAS means with the results of PF-EDAS approach and other methods.

scholarly journals Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Sen Liu ◽  
Zhilan Song ◽  
Shuqi Zhong
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Public Transportation ◽  
Group Decision ◽  
Numerical Study ◽  
Hub Location ◽  
Hub Location Problem ◽  
The Public ◽  
Multiple Attribute ◽  
Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

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.

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