Kondratenko G. Fuzzy models and algorithms for optimization of routes and trajectories in uncertainty

The thesis is devoted to development of fuzzy models, optimization algorithms and software for increasing efficiency of moveable objects' routes and trajectories in uncertainty. The main research results are: stochastic simulation models of prognoses and real nodes' parameters for modeling and optimization of routes and trajectories in uncertainty; general fuzzyfication algorithms for relatively quality input signals as fuzzy parameters of nodes; combined algorithms for decision making about including node-claimant to corresponding trajectory; rule bases' structure of fuzzy expert system for determination of satisfaction level of node's fuzzy parameters at the planned trajectory; methods for increasing efficiency of optimization processes in uncertainty for routes and trajectories by adjusting critical value of satisfaction level and search's deep for nearest node-claimants in conflict situations; criteria's estimation of route and trajectory planning in uncertainty; unification software for decisionmaking systems based on the object-oriented information technologies.