Models of Quality Estimation of Multi-Parametric Management of Complicated Systems

The author puts forward methodology of estimating and forecasting control quality in the system of managing business processes of the complicated multi-parametric system. The results of estimation are given in qualitative and quantitative forms. In order to calculate errors in control probabilistic models of false and unfound rejects were developed. For qualitative estimation of the system functioning imprecise models were developed. Probabilistic models make it possible to study the impact of statistic characteristics of modeling agents on control errors and risks. Producer’s risk and customer’s risk are considered as risks. Truthfulness and effectiveness of modeling can be checked through computer experiment on the basis of imitation algorithm. The mathematic model and the imitation algorithm have universal nature and can be used in different scientific and technical practical applications. The article describes a concrete example of estimating risks of decision-making in personnel quality management in higher education. To do this the theory of imprecise multitudes is used. To estimate the personnel quality a differentiated approach by totality of such parameters as experience, education, qualification, health, age is applied. As these parameters can hardly be estimated quantitatively, the imprecise approach on the basis of linguistic indicators is used. To combine differentiated indicators in the final integral assessment ‘human resource’ the mathematic expression was put forward. The author advanced a new multi-approach methodology of quantitative estimation of risks of decision-making in multi-parametric system of control and management through differentiated and integral functional indicators of the unit.

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