Matlab toolbox for Estimation of Distribution Algorithms (MATEDA-2.0). 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.
Keywords for this software
References in zbMATH (referenced in 5 articles , 1 standard article )
Showing results 1 to 5 of 5.
- Gao, Shujun; de Silva, Clarence W.: Estimation distribution algorithms on constrained optimization problems (2018)
- Ceberio, Josu; Irurozki, Ekhine; Mendiburu, Alexander; Lozano, Jose A.: A review of distances for the Mallows and generalized Mallows estimation of distribution algorithms (2015)
- Santana, Roberto; Bielza, Concha; Larrañaga, Pedro: Regularized logistic regression and multiobjective variable selection for classifying MEG data (2012)
- Yasser Gonzalez-Fernandez, Marta Soto: copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas (2012) arXiv
- Roberto Santana; Concha Bielza; Pedro Larrañaga; Jose Lozano; Carlos Echegoyen; Alexander Mendiburu; Rubén Armañanzas; Siddartha Shakya: Mateda-2.0: A MATLAB Package for the Implementation and Analysis of Estimation of Distribution Algorithms (2010) not zbMATH