Research On Multi-attribute Decision Making Problem Based On Uncertain Information

Multi-criteria decision-making,which includes the processing of decision information and the sorting of alternatives,is a hot research topic at present.However,in the context of big data and high-quality development,decision-making issues are becoming more and more complex,and decision makers are more inclined to express their preferences with uncertain information.Cloud model is a powerful tool for processing uncertain information,which can effectively portray the uncertainty and randomness of uncertain information with linguistic evaluation information,and the application of cloud model in decision-making problems makes decision-making results more accurate and reliable.In the uncertain information environment,combined with cloud model theory,this paper establishes multi-attribute decision-making research systems based on probabilistic uncertain linguistic and singlevalued neutrosophic linguistic.The main research work is as follows:(1)Consider the degree of similarity between the alternatives and the ideal solution,and propose the similarity measures of PUTCs and ideal solutions the probabilistic uncertain linguistic environment.In order to avoid information distortion and distortion caused by traditional methods,the Probabilistic Uncertain Trapezium Cloud(PUTC)is defined to quantify linguistic evaluation information.The similarity degree measures for PUTC is given and its properties are studied.Based on the similarity degree measures,a ranking method based on the similarity degree measures and ideal solutions is constructed,and the rationality of the method is verified by the study case and comparative analysis.(2)Considering the interrelationship between criteria and the risk attitude of decision makers,a collection and ranking method in the environment of uncertain probability information is constructed.The Probabilistic Uncertain Trapezium Cloud Weighted Bonferroni Mean(PUTCWBM)operator is defined,and the trapezium cloud score function is given based on the idea of stochastic simulation.On this basis,a decision-making method based on PUTCWBM operator is proposed,which is verified by the example of mask evaluation,and further illustrates the effectiveness and superiority of the method through sensitivity analysis,time complexity analysis and method comparison.(3)From the perspective of pairwise comparison of alternatives,a multi-attribute decision-making model under single-valued neutrosophic linguistic information environment is constructed.The conversion method of single-valued neutrosophic linguistic number and trapezium cloud is introduced.On this basis,the likelihood and dominance relationship of trapezium cloud are defined,and its properties are analyzed.Considering the interaction between the individual influence of evaluation information and the criterion,a criterion weight solution model based on likelihood difference and entropy theory is given,and an extended Alternative Queuing Method(AQM)method based on likelihood is proposed,the feasibility and effectiveness of the weight determination method and the extended AQM method are verified by an example of shared bicycle evaluation.The multi-attribute decision-making model constructed in this paper cuts into the problem from three perspectives: optimal solution similarity,aggregation and pairwise comparison of alternatives,enriches the theoretical knowledge of cloud model group decisionmaking,and expands the solution ideas and methods for multi-attribute decision-making problems,has certain theoretical and practical significance.