Khomyakova N. Stochastic models, methods and the information technology of company's development forecasting and management

The object of research is the process of the company management in conditions of instability. The purpose of research is the increasing of planning and management efficiency of the commodity production volume in unstable conditions on the basis of forecasting and stochastic modeling of the production development. The main research methods are the methods of the statistical theory of parameters and processes estimations; Kalman filter method; dynamic systems management methods with quadratic yardstick of an optimality; the method of simulation modeling of commodity production volume management in instabile conditions; object-oriented information technologies. The scientific result of the outcomes consists in development of the method of multicomponent time series adaptive estimation and forecasting and management processes technology in conditions of instability according to the production development problem. The practical result is that the models and methods elaborated in the dissertation arethe scientific-methodical basis for creation of the computer subsystem of forecasting and management of the production development for ASUP. For the first time the method of adaptive estimation and forecasting of the main parameters which are determined the production development, basing on polynomial-autoregressive models, which one as against existing the components cancellation for iterative refinement of their characteristics is used, that provides heightened accuracy of forecasting for automatic planning of the production development is developed. The dynamic model of production volume change is improved by the taking into account the random disturbances and observation errors, and also by vectors extension of production state and control functions, that allows to automize the management of the commodity production volume on the basis of correcting measures calculation. The information technology of simulation modeling of production volume management has received further development on the basis of elaborated stochastic models, by taking into account the speed of its change and usage of quadratic yardstick of an optimality, that enables by definition of deviations of production volumes actual values from scheduled to calculate needed value of additional financing for minimization of these deviations. The intridaction is branch-based. Further usage of the outcomes, obtained in the work, is expedient in analytical departments and departments of strategic development in the research, project and manufacturing organizations