Stationary probability density of stochastic search processes in global optimization
Artificial Intelligence
2008-01-30 v1 Statistical Mechanics
Neural and Evolutionary Computing
Abstract
A method for the construction of approximate analytical expressions for the stationary marginal densities of general stochastic search processes is proposed. By the marginal densities, regions of the search space that with high probability contain the global optima can be readily defined. The density estimation procedure involves a controlled number of linear operations, with a computational cost per iteration that grows linearly with problem size.
Cite
@article{arxiv.0710.3561,
title = {Stationary probability density of stochastic search processes in global optimization},
author = {Arturo Berrones},
journal= {arXiv preprint arXiv:0710.3561},
year = {2008}
}