EXPERT DECISION-MAKING SYSTEMS

An approach to making complex technical and economic decisions is proposed in cases where there is insufficient (or no) information about the experimental statistical data necessary for the construction of regression models of criterion functions. The situation is aggravated when a decision is made according to several conflicting quality criteria. In conditions of an acute shortage of experimental data, it is proposed to obtain the necessary information («quasi-experimental» data) from experts - specialists with sufficient experience in making decisions for the class in question. A qualified specialist (expert) with sufficient experience in making decisions for this class can perform a thought experiment. He must imagine what, in his opinion, the levels of criterion functions will be at various reference points of factors. The method is based on an individual opinion (postulate), expressed by a specialist-expert about the estimated value, based on his professional experience. To assess a certain quantitative characteristic, the postulates of not one, but several persons competent in this issue are used. It is assumed that the «true» value of the unknown quantitative characteristic is within the range of expert assessments and the «generalized» collective opinion is more reliable. To solve the problem under consideration, a multicriteria optimization approach is taken using a nonlinear trade-off scheme. This study makes it possible to identify the main trends in the development of multi-criteria decision-making systems in the absence (or lack) of experimental data. A model example is given.