Conflict Analysis of Extension Group Decision-Making Based on D-S Evidence Theory

2011 ◽  
Author(s):  
Jiajun Zhu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Evidence Theory ◽  
Conflict Analysis ◽  
Extension Group

A cosine similarity measure for multi-criteria group decision making under neutrosophic soft environment

2020 ◽  
Vol 39 (5) ◽  
pp. 7863-7880
Author(s):  
Yuanxiang Dong ◽  
Xiaoting Cheng ◽  
Weijie Chen ◽  
Hongbo Shi ◽  
Ke Gong
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Group Decision Making ◽  
Group Decision ◽  
Evidence Theory ◽  
Cosine Similarity ◽  
Uncertain Information ◽  
Soft Sets ◽  
Cosine Similarity Measure ◽  
Credibility Degree

In actual life, uncertain and inconsistent information exists widely. How to deal with the information so that it can be better applied is a problem that has to be solved. Neutrosophic soft sets can process uncertain and inconsistent information. Also, Dempster-Shafer evidence theory has the advantage of dealing with uncertain information, and it can synthesize uncertain information and deal with subjective judgments effectively. Therefore, this paper creatively combines the Dempster-Shafer evidence theory with the neutrosophic soft sets, and proposes a cosine similarity measure for multi-criteria group decision making. Different from the previous studies, the proposed similarity measure is utilized to measure the similarity between two objects in the structure of neutrosophic soft set, rather than two neutrosophic soft sets. We also propose the objective degree and credibility degree which reflect the decision makers’ subjective preference based on the similarity measure. Then parameter weights are calculated by the objective degree. Additionally, based on credibility degree and parameter weights, we propose the modified score function, modified accuracy function, and modified certainty function, which can be employed to obtain partial order relation and make decisions. Later, we construct an aggregation algorithm for multi-criteria group decision making based on Dempster’s rule of combination and apply the algorithm to a case of medical diagnosis. Finally, by testing and comparing the algorithm, the results demonstrate that the proposed algorithm can solve the multi-criteria group decision making problems effectively.

Method for Two-People Multiple-Attribute Decision Making and its Application

2011 ◽  
Vol 204-210 ◽  
pp. 2061-2064
Author(s):  
Fang Wei Zhang ◽  
Shi He Xu ◽  
Bao Shi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Evidence Theory ◽  
Multiple Attribute Decision Making ◽  
New Method ◽  
Multiple Attribute

In this paper we study the multi-attribute group decision-making problems and put forward a kind of method. In this method, based on clustering evidence theory, the decision-making information is translated into evidences to support different decision-making program. Then, by the amount of evidences, decision-making program ranking is completed. The method’s character can not only rank the decision-making programs by their merits, but also give each program the probability to be the best. Finally, an example is given to show the rationality and effectiveness of the new method.

A Multi-Attribute Group Decision-Making Method Based on Linguistic Intuitionistic Fuzzy Numbers and Dempster–Shafer Evidence Theory

2020 ◽  
Vol 19 (02) ◽  
pp. 499-524 ◽  
Author(s):  
Peide Liu ◽  
Xiaoxiao Liu ◽  
Guiying Ma ◽  
Zhaolong Liang ◽  
Changhai Wang ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Programming Model ◽  
Comprehensive Evaluation ◽  
Evidence Theory ◽  
Intuitionistic Fuzzy Numbers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy

In this paper, we propose a multi-attribute group decision-making (MAGDM) method based on Dempster–Shafer Evidence Theory (DST) and linguistic intuitionistic fuzzy numbers (LIFNs), in which both the expert weights and attribute weights are unknown. Firstly, we represent LIFNs as basic probability assignments (BPAs) by DST based on linguistic scale function (LSF), and a linear programming model is proposed to combine the objective weights and subjective weights of attributes to obtain the combined weights. At the same time, the experts’ weights are obtained through Jousselme distance. Secondly, we use the weights to correct the evidence, and the comprehensive evaluation value of each alternative is calculated by the combination rule of evidence. Further, a new MAGDM approach with DST and LIFNs is presented. Finally, we give an example to explain the proposed method and compare it with other methods to show the feasibility and superiority.

Sign in / Sign up

Export Citation Format

Share Document