| The research of multiple attribute decision making is becoming more and more mature,but because of the complexity,uncertainty,people’s fuzziness thinking and fuzziness of evaluation value,the research on multiple attribute decision making has been aroused widely concern in academia.Fuzziness and randomness are unavoidable in the research of multiple attribute decision making but directly affect the accuracy of evaluation results.In order to solve this problem properly,cloud model theory is introduced in this research.In this study firstly analyzes the general methods and theoretical basis of multiple attribute decision making,the fuzziness and randomness in multiple attribute decision making.Comparing and analyzing the common methods of solving uncertainty,and puts forward the idea of using cloud theory to solve the uncertainty problem.The feasibility and credibility of the cloud model in realizing the qualitative value to the quantitative value conversion are clarified,and the general method is validated by comparing the examples.Secondly,in this paper analyzes the common method of weight determination,then puts forward a method of weight determination based on cloud model,establishes two kinds of optimization models with three digital features of cloud model,optimizes and determines the weights of each attribute,and synthesizes the subjective and objective weights.And then sorts the results by contrasting the subjectivity weights,objective weight ranking results and comprehensive ranking results verify the credibility of comprehensive weights.Finally,we extend the multiple attribute decision making method based on cloud model,based on the cloud model of the interval number of multiple attribute decision making algorithm,based on cloud model of triangular fuzzy number of multi-attribute decision making algorithm,based on cloud model of hybrid multiple attribute decision making algorithm,the algorithm for the interval number of the transformation model is modified,For the conversion model of triangular fuzzy number,this paper abandons the existing point-type conversion model,uses integral function to ensure the accuracy of information,and verifies its feasibility by example one by one. |
