Abstract:
It is shown that practical decision-making problems often involve taking into account preferences not fully identified, as well as uncertain factors. Known approaches to the analysis of such problems are based on introducing of quantitative probabilities and using of utility function. However, this requires obtaining rather complex and therefore unreliable and not always available information. In this paper, such methods are proposed for analyzing decisions under uncertainty, for the implementation of which utility functions and quantitative probabilities are not required. They are based on the ideas and results of the theory of the importance of criteria in multi-criteria problems of decision-making under certainty. Partial preference and indifference relations generated by qualitative probability on a set of strategies are used. Computational methods for constructing such relations are considered. Calculation examples are given.
Keywords:decision-making under uncertainty, incomplete information about preferences and uncertain factors, preference relations, qualitative probability.