On convergence rate of a rectangular partition based global optimization algorithm

Authors

James Calvin, Department of Computer Science
Gražina Gimbutienė, Vilniaus Universitetas
William O. Phillips, Department of Computer Science
Antanas Žilinskas, Vilniaus Universitetas

Document Type

Article

Publication Date

5-1-2018

Abstract

The convergence rate of a rectangular partition based algorithm is considered. A hyper-rectangle for the subdivision is selected at each step according to a criterion rooted in the statistical models based theory of global optimization; only the objective function values are used to compute the criterion of selection. The convergence rate is analyzed assuming that the objective functions are twice- continuously differentiable and defined on the unit cube in d-dimensional Euclidean space. An asymptotic bound on the convergence rate is established. The results of numerical experiments are included.

Identifier

85042945079 (Scopus)

Publication Title

Journal of Global Optimization

External Full Text Location

https://doi.org/10.1007/s10898-018-0636-z

e-ISSN

15732916

ISSN

09255001

First Page

165

Last Page

191

Issue

1

Volume

71

Grant

0926949

Fund Ref

National Science Foundation

Recommended Citation

Calvin, James; Gimbutienė, Gražina; Phillips, William O.; and Žilinskas, Antanas, "On convergence rate of a rectangular partition based global optimization algorithm" (2018). Faculty Publications. 8692.
https://digitalcommons.njit.edu/fac_pubs/8692