Bayesovské evoluční algoritmy s aplikacemi v úlohách dekompozice a alokace, zkrácená verze habilitační práce

Multiobjective optimization problems, decomposition and allocation problems, classical optimization methods, genetic algorithms, probabilistic models, bivariate marginal distribution algorithm, bayesian networks, Bayesian-Dirichlet metric, binary decision diagrams, scoring metrics, bayesian evolutionary algorithms.

The habilitation thesis "Bayesian evolutionary algorithms applied in decomposition and allocation problems" deals with the design, analysis and applications of Bayesian evolutionary algorithms for the solution of complex almost NP-complete combinatorial optimization problems mainly from the area of decomposition and allocation of graph structures. Bayesian evolutionary algorithms are advanced evolutionary algorithms based on the probabilistic graph models. These algorithms lack the well known problem of the standard genetic algorithms with the convergence and the drawback arising from the requirement on the specification of the control parameters and genetic operators.