Convergence rate of a rectangular subdivision-based optimization algorithm for smooth multivariate functions
Document Type
Article
Publication Date
5-1-2022
Abstract
In Zheng (J. Glob. Opt. 79:431-445;2021) the authors described a global optimization algorithm for multivariate continuous functions and applied it to an image processing problem. While the algorithm was shown to converge for all continuous functions, the convergence rate was not established. In this paper we assume that the objective function is smooth, and establish the asymptotic convergence rate when the algorithm is applied to such a function.
Identifier
85112297719 (Scopus)
Publication Title
Optimization Letters
External Full Text Location
https://doi.org/10.1007/s11590-021-01792-3
e-ISSN
18624480
ISSN
18624472
First Page
1137
Last Page
1151
Issue
4
Volume
16
Grant
CMMI-1562466
Fund Ref
National Science Foundation
Recommended Citation
Zheng, Cuicui and Calvin, James, "Convergence rate of a rectangular subdivision-based optimization algorithm for smooth multivariate functions" (2022). Faculty Publications. 2962.
https://digitalcommons.njit.edu/fac_pubs/2962
