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FIT-EVOAcad. year: 2013/2014
Multiobjective optimization problems, standard approaches and stochastic evolutionary algorithms (EA), simulated annealing (SA). Evolution strategies (ES) and genetic algorithms (GA). Tools for fast prototyping. Representation of problems by graph models. Evolutionary algorithms in engineering applications namely in synthesis and physical design of digital circuits, artificial intelligence, signal processing, scheduling in multiprocessor systems and in business commercial applications.
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branch MBS , 0 year of study, summer semester, electivebranch MIN , 0 year of study, summer semester, electivebranch MIS , 0 year of study, summer semester, electivebranch MMI , 0 year of study, summer semester, electivebranch MMM , 0 year of study, summer semester, electivebranch MPV , 2 year of study, summer semester, compulsory-optionalbranch MBI , 0 year of study, summer semester, compulsory-optionalbranch MGM , 0 year of study, summer semester, electivebranch MSK , 0 year of study, summer semester, elective
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