Stopping rules in k-adaptive global random search algorithms

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. Keywords Global random search · global optimization · extreme order statistics · waiting times · k-th order statistic

• Type: Journal
• Year: 2010
• Where: JGO
• Authors: Anatoly A. Zhigljavsky, Emily Hamilton
• Keywords: Global Random Search, JGO 2010, Order Statistic, Statistical Procedures