arXiv · 0901.0597
On the Optimal Convergence Probability of Univariate Estimation of Distribution Algorithms
Abstract
In this paper, we obtain bounds on the probability of convergence to the optimal solution for the compact Genetic Algorithm (cGA) and the Population Based Incremental Learning (PBIL). We also give a sufficient condition for convergence of these algorithms to the optimal solution and compute a range of possible values of the parameters of these algorithms for which they converge to the optimal solution with a confidence level.
Explore related subjects
Keep this discovery
Reza Rastegar. 2009-01-06. On the Optimal Convergence Probability of Univariate Estimation of Distribution Algorithms. https://arxiv.org/abs/0901.0597
Cite the original work for its findings. Save a collection to share your selection of sources.