scholarly journals Grey Situation Group Decision-Making Method Based on Prospect Theory

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Na Zhang ◽  
Zhigeng Fang ◽  
Xiaqing Liu
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Value Function ◽  
Group Decision ◽  
Reference Points ◽  
Final Decision ◽  
Topsis Method ◽  
Psychological Behavior ◽  
Ideal Situation

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts’ risk preference into grey situation decision-making to make the final decision be more in line with decision experts’ psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts’ evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.

Doubly Extended Fuzzy TOPSIS Method for Group Decision Making

2019 ◽  
Vol 66 (1) ◽  
pp. 27-50
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Final Decision ◽  
Topsis Method ◽  
Decision Matrix

Multiple Criteria Decision Making methods, such as TOPSIS, have become very popular in recent years and are frequently applied to solve many real-life situations. However, the increasing complexity of the decision problems analysed makes it less feasible to consider all the relevant aspects of the problems by a single decision maker. As a result, many real-life problems are discussed by a group of decision makers. In such a group each decision maker can specialize in a different field and has his/her own unique characteristics, such as knowledge, skills, experience, personality, etc. This implies that each decision maker should have a different degree of influence on the final decision, i.e., the weights of decision makers should be different. The aim of this paper is to extend the fuzzy TOPSIS method to group decision making. The proposed approach uses TOPSIS twice. The first time it is used to determine the weights of decision makers which are then used to calculate the aggregated decision matrix for all the group decision matrices provided by the decision makers. Based on this aggregated matrix, the extended TOPSIS is used again, to rank the alternatives and to select the best one. A numerical example illustrates the proposed approach.

scholarly journals A Hesitant Fuzzy Multi-Attribute Group Decision Making Method Based on Prospect Theory

2018 ◽  
Vol 36 (4) ◽  
pp. 735-741
Author(s):  
Peng Sun ◽  
Jun Zhang ◽  
Hongbin Zeng
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Reference Points ◽  
Fuzzy Decision Making ◽  
Entropy Weight ◽  
Attribute Weight ◽  
Single Attribute ◽  
Entropy Weight Method

To solve a multi-attribute group decision-making problem, since its attribute weight is completely unknown, based on the prospect theory, a hesitant fuzzy multi-attribute group decision making method is proposed. According to the single-attribute-preference function provided by a decision maker, an improved entropy weight method is proposed to calculate the attribute weight. The hesitant fuzzy decision-making matrix is transformed into the prospect decision-making matrix which utilizes positive and negative ideal solutions as reference points. Then alternative schemes are ranked according to the ratio of profit to loss. Finally, a numerical example is provided to verify the effectiveness and feasibility of the proposed method.

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.

Reducing the Risk of Wrong Choice in Group Decision Making by Optimal Weight Allocating to Decision Makers

2018 ◽  
Vol 7 (2) ◽  
pp. 1-23 ◽  
Author(s):  
Mohammad Azadfallah
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Potential Risk ◽  
Group Decision ◽  
Decision Makers ◽  
Topsis Method ◽  
Numerical Examples ◽  
Multiple Attribute ◽  
Key Issues ◽  
The Ideal

How to determine a weight for decision makers (DMs) is one of the key issues in Multiple Attribute Group Decision Making (MAGDM). While, some experts (or DMs) clearly wiser and more powerful in such matters than others, it has often seen that experts play their roles with same weights of importance. Meanwhile, it will lead to the wrong choice (or decision risk) and loss of values. Since, in the absence of any other standards about how to reduce this potential risk for bias, in this article, based on judgment matrices and error analysis, the author presents two new algorithm taken from crisp (the correlation-based approach) and interval (the ideal-based approach) TOPSIS method, respectively. Finally, two numerical examples are given to demonstrate the feasibility of the developed method.

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