Modeling and Identification in the Problems of Multicriteria Optimization with Linear and Quadratic Performance Criteria under Statistical Uncertainty

摘要

Various methods of unknown parameters identification in the problems of multicriteria optimization under uncertainty with linear and quadratic objective function have been proposed. Parametric identification was made in framework of discrete-continuous models with dummy variables and multiple logit-model. Also there was developed the approach which is based on the construction of functional forms and includes the effects of the second order.