E. M. Sukharev, V. G. Kuznetsov, V. I. Soloviev

Due to the fact that a clear model of optimization and decision-making is generalized to the fuzzy case, and psychologically the decision maker, it is more convenient to work with the linguistic representation of information, considered the class of models. When linguistic approach to multi-criteria decision making problems may not be justified in phasing out assessments of individual characteristics in a generalized assessment of using certain algebraic operations, and the immediate consideration of a single estimate, which depends on many parameters. Any alternative is described by the fuzzy area in the multidimensional space of interacting traits. Each alternative corresponds to a utility value, which is given qualitatively, linguistically. Also, when optimizing management decisions of interest to a fuzzy model that takes into account the information component. The formalized description of the system must take into account the level of information about it. By characteristics, which can serve as a measure of the quality of information provided by the fuzzy sets are the indices of fuzziness, inaccuracies, and conditionality. Systems proposed to be classified on three criteria: information index of fuzziness, the type of fuzziness and ambiguity of the order. Index of fuzziness characterizes the level of information about the system and takes into account components such as accuracy, reliability, completeness, importance, degree of formalization of fuzziness. Order of fuzziness shows how well designed the system and determined by the number of fuzzy hierarchical levels in the overall structure. The proposed approach makes it possible to classify the system under fuzzy information about them to their relative ranking in terms of information that will enable to build a model of optimal coverage by new information technologies collectively the tasks entrusted to decision support systems.