Stopping rules in k-adaptive global random search algorithms

被引：0
|
作者：
Anatoly Zhigljavsky
Emily Hamilton
机构：
[1] Cardiff University,School of Mathematics
来源：
Journal of Global Optimization | 2010年 / 48卷
关键词：
Global random search; Global optimization; Extreme order statistics; Waiting times; -th order statistic;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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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页码：87 / 97
页数：10
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