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.
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Zhigljavsky, A., Hamilton, E. Stopping rules in k-adaptive global random search algorithms. J Glob Optim 48, 87–97 (2010). https://doi.org/10.1007/s10898-010-9528-6
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DOI: https://doi.org/10.1007/s10898-010-9528-6