Detail výsledku
Estimation Distribution Algorithm for mixed continuous-discrete optimization problems
Schwarz Josef, doc. Ing., CSc.
In recent few years expressive progress in the theory and practice of Estimation of Distribution Algorithms (EDAs) [1] has appeared, where the classical genetic recombination operators are replaced by probability estimation and stochastic sampling techniques. In this paper we identify some disadvantages of present probabilistic models used in EDAs and propose more general and efficient model for continuous optimization problems based on the decision trees. The new variant of EDA is capable to solve mixed continuous-discrete optimization problems.
Estimation Distribution Algorithm, Bayesian Optimization Algorithm, Bayesian network, Gaussian network, classification and regression tree model (CART).
@inproceedings{BUT10030,
author="Jiří {Očenášek} and Josef {Schwarz}",
title="Estimation Distribution Algorithm for mixed continuous-discrete optimization problems",
booktitle="Proceedings of the 2nd Euro-International Symposium on Computational Intelligence",
year="2002",
pages="227--232",
publisher="IOS Press",
address="Kosice",
isbn="1-58603-256-9"
}