A dynamic stochastic decision-making method based on discrete time sequences

•We analyse 3 different dynamic stochastic decision-making methods.•We propose a new method for handling discrete time sequences.•We account for unequal time intervals using the exponential decay model.•The new method is tested empirically and shown to be practical and effective.

This paper studies a dynamic stochastic decision-making method based on discrete time sequences. With the aim of rectifying the deficiency of calculation methods that use only the “sequence” information in the determination of discrete time sequence weight, we first propose a discrete time sequence weight calculation method that can deal with unequal time intervals by introducing an exponential decay model, and gather the original dynamic stochastic decision information according to the timing weight and attribute weight. Second, considering the disadvantages of decision criteria such as traditional stochastic dominance, stochastic multi-criteria acceptability analysis, and connection number of set pair analysis, in the absence of original information and limited conditions, we propose a decision method based on possibility, convert this information into interval numbers based on the theory of stochastic probability distribution, and then rank the order of the scheme using the possibility model of interval numbers. Finally, we test the effectiveness and reasonableness of the method by empirical calculation and show that the proposed method is both practical and effective.