NONLINEAR PROGRAMMING IN MODELLING INFORMATION SYSTEMS
Ncrease of efficiency of designing of information system of the organization in conditions of uncertainty and risk is an actual problem. Methods of the theory of research of operations are applied to the decision of a problem. The method of designing of information systems in conditions of risk is developed. The method of designing is based on development of nonlinear mathematical model of information system. The problem of conditional optimization is formulated. The optimum decision of a problem is defined by method of Lagrange. The essence of method of Lagrange consists in data of a problem of search of a conditional extremum of criterion function on set of admissible values to a problem of unconditional optimization of function. The algorithm of method of Lagrange includes three stages. At the first stage function of Lagrange is made. At the second stage private derivatives are defined. At the third stage the conditional extremum of function is defined. Method of Lagrange allows to pass from conditional optimization to unconditional optimization and to expand means of the decision of a problem. Definition of the optimum project of information system in conditions of risk is carried out on an example of central administrative board of social protection of the population on Kurgan region. The group of projects of the information system, including five variants is formed. Efficiency of projects of information systems are random variables. The population mean and a dispersion of projects are known sizes. Value of average efficiency of group of projects of information systems is set by the person making a decision. The shares of financing of the projects are required to define. The shares of financing of the projects are minimized a dispersion of projects of information system. The nonlinear mathematical model is resulted and the optimum decision is defined. Application of the developed method allows to reduce financial expenses and terms of designing of information systems in conditions of risk and to raise validity of accepted decisions at the design stage.