Sidenko I. Fuzzy models and information technologies for increasing efficiency of decision-making in transport logistics under uncertainty

Object of study - processes of fuzzy information processing and decision-making in the optimization of cargo transportation under uncertainty. Purpose - to increase the efficiency of multicriterion decision making problems of transport logistics through the development and research of fuzzy models, algorithms, information technologies and DSS software. Methods: numerical methods; methods of processing fuzzy expert information; methods of fuzzy sets; methods and principles of functional programming. Novelty - first proposed the concept of classification analysis tasks and stages of transport logistics; first proposed two-stage correction method of fuzzy knowledge bases of intelligent DSS for transport logistics; further developed the mechanism of structural reconfiguration of fuzzy DSS; further developed the method of aggregation incoming expert information with a high level of uncertainty; improved optimization method pendulum ring and transport routes, taking into account return blank runs. The results of the research, developed new models, methods and information technologies to increase the efficiency of multicriterion decision making problems of transport logistics under uncertainty.