Local tuning and partition strategies for diagonal GO methods
Optimization and Control
2011-03-21 v1 Numerical Analysis
Numerical Analysis
Computational Physics
Abstract
In this paper, global optimization (GO) Lipschitz problems are considered where the multi-dimensional multiextremal objective function is determined over a hyperinterval. An efficient one-dimensional GO method using local tuning on the behavior of the objective function is generalized to the multi-dimensional case by the diagonal approach using two partition strategies. Global convergence conditions are established for the obtained diagonal geometric methods. Results of a wide numerical comparison show a strong acceleration reached by the new methods working with estimates of the local Lipschitz constants over different subregions of the search domain in comparison with the traditional approach.
Cite
@article{arxiv.1103.3665,
title = {Local tuning and partition strategies for diagonal GO methods},
author = {Dmitri E. Kvasov and Clara Pizzuti and Yaroslav D. Sergeyev},
journal= {arXiv preprint arXiv:1103.3665},
year = {2011}
}
Comments
15 pages, 4 figures