Convergence rate of a rectangular subdivision-based optimization algorithm for smooth multivariate functions

Cuicui Zheng; James Calvin

doi:10.1007/s11590-021-01792-3

Convergence rate of a rectangular subdivision-based optimization algorithm for smooth multivariate functions

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	1137-1151
Number of pages	15
Journal	Optimization Letters
Volume	16
Issue number	4
DOIs	https://doi.org/10.1007/s11590-021-01792-3
State	Published - May 2022
Externally published	Yes

All Science Journal Classification (ASJC) codes

Control and Optimization
Business, Management and Accounting (miscellaneous)

Keywords

Convergence
Global optimization
Smooth functions

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10.1007/s11590-021-01792-3

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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.",

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author = "Cuicui Zheng and James Calvin",

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AB - 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.

KW - Convergence

KW - Global optimization

KW - Smooth functions

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Convergence rate of a rectangular subdivision-based optimization algorithm for smooth multivariate functions

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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