Dynamic grey stochastic decision-making method based on Markov chain and “matching” thought

In view of dynamic multi-criteria decision-making problems, in which the criteria value of alternatives are three-parameters interval numbers and criteria exists different natural states, a dynamic grey stochastic multi-criteria decision-making method is proposed. According to the stationary distribution thought of Markov chain, the final state of natural possibility is obtained. The time information is concentrated by calculating the importance of time function. On this basis, the three-unit connection number of three-parameter interval number is defined, and the optimization models based on single to noise ratio theory are constructed and solved according to the interactive interference of alternatives. Then, the comprehensive criteria weights are given based on the compromise thought, and alternatives are sorted by comparing the values of satisfaction of single to noise. Finally, An illustrative example shows the feasibility and rationality of the proposed approach.