Stopping rules in k-adaptive global random search algorithms

Zhigljavsky, Anatoly Alexandrovich ORCID: https://orcid.org/0000-0003-0630-8279 and Hamilton, Emily 2010. Stopping rules in k-adaptive global random search algorithms. Journal of Global Optimization 48 (1) , pp. 87-97. 10.1007/s10898-010-9528-6

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Abstract

In this paper we develop a methodology for defining stopping rules in a general class of global random search algorithms that are based on the use of statistical procedures. To build these stopping rules we reach a compromise between the expected increase in precision of the statistical procedures and the expected waiting time for this increase in precision to occur.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Publisher:	Springer
ISSN:	1573-2916
Last Modified:	18 Oct 2022 13:44
URI:	https://orca.cardiff.ac.uk/id/eprint/15205

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