Matlab toolbox for Estimation of
Distribution Algorithms (MATEDA2.0)
The package allows the optimization of single and multi-objective
problems with estimation of distribution algorithms (EDAs)
based on undirected graphical models and Bayesian networks. The
implementation is conceived for allowing the incorporation by the user
of different combinations of selection, learning, sampling, and local
search procedures. Other included methods allow the
analysis of the structures learned by the probabilistic models,
the visualization of particular features of these structures and the use of the probabilistic models as fitness modeling tools.