Research On Group Consensus In Linguistic Fuzzy Multi-attribute Group Decision-making

In linguistic fuzzy multi-attribute group decision making,fuzzy linguistic terms are used to describe the preference information of decision makers,which has the characteristics of intuition and flexibility,and has been widely used.In order to make the results of group decision-making acceptable,it is necessary to study the problem of group consensus.In this paper,a new measure formula of group consensus degree is proposed.In view of the shortcomings of triangular fuzzy number semantics and interval-value triangular fuzzy semantics commonly used in linguistic term set,a interval-value triangular fuzzy semantics with parameters of linguistic term set is constructed by level cut set based on the decomposition theorem of fuzzy sets.A mathematical optimization model for maximizing the degree of group consensus is established and solved.A new method of determining interval-value triangular fuzzy semantics is proposed,which is applied to the failure mode risk analysis of A-frame and boom components.The main research work and results are as follows:1.By investigating the relevant literatures at home and abroad,this paper reviews the definitions and properties of fuzzy numbers,linguistic term set and semantics,introduces particle swarm optimization algorithm and the process of existing group consensus,and briefly describes the application of grey correlation analysis and fuzzy Borda ordinal value method in risk analysis.2.A new distance measure of interval-value triangular fuzzy number is defined,and on this basis,the measure formula of group consensus is given;the interval-value triangular fuzzy number semantics with parameters of linguistic term set is constructed by introducing level cut set;the shortcomings of the original method are pointed out comparing with the commonly used seven-dimensional triangular fuzzy semantics and interval triangular fiuzzy semantics by numerical examples to validate the method is effective.3.Based on the interval-value triangular fuzzy number semantics with parameters,a mathematical optimization model is established to maximize the degree of group consensus,and the parameters and principal points are solved by particle swarm optimization algorithm,thus the interval-value triangular fuzzy number semantics is obtained.By using this method,the interval-value triangular fuzzy number semantics with arbitrary granularity can be determined.The validity of the optimization model in improving the degree of group consensus is illustrated by numerical examples based on the comparison of individual deviation.4.A-frame and boom components in the main structure system of LIUHUA10-1 CEP crane of offshore platform are investigated on site,and 13 failure modes of A-frame and boom components are evaluated by three teams under three risk assessment indicators.According to the interval-value triangular fuzzy number semantics,the comprehensive risk ranking of failure modes is obtained by grey correlation analysis-fuzzy Borda ordinal value method.