scholarly journals A Combined Weighting Method Based on Hybrid of Interval Evidence Fusion and Random Sampling

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Ying Yan ◽  
Bin Suo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Random Sampling ◽  
Probability Function ◽  
Group Decision ◽  
Evidence Theory ◽  
Cumulative Probability ◽  
Weighting Method ◽  
High Conflict ◽  
Weighting Problem

Due to the complexity of system and lack of expertise, epistemic uncertainties may present in the experts’ judgment on the importance of certain indices during group decision-making. A novel combination weighting method is proposed to solve the index weighting problem when various uncertainties are present in expert comments. Based on the idea of evidence theory, various types of uncertain evaluation information are uniformly expressed through interval evidence structures. Similarity matrix between interval evidences is constructed, and expert’s information is fused. Comment grades are quantified using the interval number, and cumulative probability function for evaluating the importance of indices is constructed based on the fused information. Finally, index weights are obtained by Monte Carlo random sampling. The method can process expert’s information with varying degrees of uncertainties, which possesses good compatibility. Difficulty in effectively fusing high-conflict group decision-making information and large information loss after fusion is avertible. Original expert judgments are retained rather objectively throughout the processing procedure. Cumulative probability function constructing and random sampling processes do not require any human intervention or judgment. It can be implemented by computer programs easily, thus having an apparent advantage in evaluation practices of fairly huge index systems.

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.

scholarly journals Group Decision-making Method Based on Grey Relational Analysis and Evidence Theory for XAI

2021 ◽  
Author(s):  
Decai Sun ◽  
Dang Luo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Grey Relational Analysis ◽  
Group Decision ◽  
Evidence Theory ◽  
Mass Function ◽  
Decision Makers ◽  
Relational Analysis ◽  
Grey Relational ◽  
Ranking Analysis

Abstract For the uncertainty and complexity ingroup decision making and the differences of decision makers’ reliabilities, a group decision making method based on grey relational analysis and evidence theory is proposed. Combining grey relational analysis with evidence theory, a novel decision-making method extracting the degree of ignorance for individual decision makers’ information and constructing the Mass function is presented based on the comprehensive grey relational analysis (CGRA) method. We should also address how AI systems make their black box decisions, which calls for research into Explainable AI (XAI) by pursuing reverse engineering and self-explainability in AI. Considering the differences of decision makers’ reliabilities, the Mass function is modified by the evidence weight, and the group decision information is fused by the Dempster’s combination rule. On this basis, the Mass function is further transformed into the probability by the Pignistic probability transformation, which issued for ranking analysis of group decision making. Finally, the proposed method is applied to the green supplier selection, and the comparative analysis is further performed to verify the rationality and effectiveness of the proposed method.

scholarly journals A Competitive Multiattribute Group Decision-Making Approach for the Game between Manufacturers

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Quan Zhang ◽  
KeXin Jiang ◽  
ManTing Yan ◽  
JiYun Ma
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Evidence Theory ◽  
Practical Case ◽  
Game Matrix ◽  
Decision Making Problem ◽  
Dimension 2 ◽  
Evaluation Information

Under the competitive market environment, the game between manufacturers comes down to the competitive multiattribute group decision-making problem. In this study, the evaluation information of experts is given in the form of 2-dimension 2-tuple linguistic variables, and an approach is proposed for the competitive multiattribute group decision-making problem based on game theory and evidence theory. Firstly, based on the evidence theory, the attribute values of each situation are obtained by aggregating the 2-dimension 2-tuple linguistic evaluation information given by experts. Secondly, according to the attribute values of every situation, the evidence theory is applied for the second aggregation to obtain the overall values of every situation, and then the game matrix of competitive multiattribute group decision problem is formed. Then, according to the bivariate game matrix, the Nash equilibrium point of competitive multiattribute group decision-making problem is determined based on game theory. Finally, a practical case about the alternative selections for a duopoly problem is used to illustrate the effectiveness and applicability of the proposed approach for the competitive multiattribute group decision-making problem.

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