Control in intelligent systems which handle the optimizational decision support problems was considered. A new line of research, modeling of evolution and genetic search, was proposed for it. The main principles of evolution in artificial systems were studied. Strategies of interaction of the search methods and evolutionary modeling were presented. Nonstandard control architectures for solving the optimizational decision support problems were constructed, which enables one to parallelize the process of search of the optimizational decision support problems and obtain the set of local optima in a polynomial time. Complexity of the algorithms has a quadratic order.
KeywordsMechanical Engineer Decision Support System Theory Evolutionary Modeling Polynomial Time
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