期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2016
卷号：15
期号：1
页码：47
出版社：Wayne State University
摘要：Designing a tightened normal tightened sampling plan requires sample sizes and acceptance number with switching criterion. An evolutionary algorithm, the genetic algorithm, is designed to identify optimal sample sizes and acceptance number of a tightened normal tightened sampling plan for a specified consumer’s risk, producer’s risk, and switching criterion. Optimal sample sizes and acceptance number are obtained by implementing the genetic algorithm. Tables are reported for various choices of switching criterion, consumer’s quality level, and producer’s quality level.
关键词：tightened normal tightened sampling plan; average outgoing quality; switching criterion; genetic algorithm.
