首页> 外文期刊>International journal of multicriteria decision making >Multi-objective Markov-based economic-statistical design of EWMA control chart using NSGA-Ⅱ and MOGA algorithms
【24h】

Multi-objective Markov-based economic-statistical design of EWMA control chart using NSGA-Ⅱ and MOGA algorithms

机译:基于NSGA-Ⅱ和MOGA算法的EWMA控制图基于马尔可夫多目标经济统计设计

获取原文
获取原文并翻译 | 示例
       

摘要

The exponentially weighted moving average (EWMA) control charts are useful for detecting small shifts in the process mean. In this paper, we investigate multi-objective economic-statistical design of the EWMA control charts and propose two evolutionary algorithms including non-dominated sorting genetic algorithm (NSGA-Ⅱ) and multi-objective genetic algorithm (MOGA) to determine the optimal chart parameters. The cost function used in this paper is Lorenzen and Vance cost function. We also used quadratic Taguchi loss function to determine the costs of producing non-conforming items under both in-control and out-of-control situations. The average run length values in both in-control and out-of-control states are computed by using Markov chain approach. A numerical example is applied to compare the results of proposed algorithms in finding the Pareto optimal solution of the multi-objective economic-statistical model. Finally, a sensitivity analysis on the economic and the statistical criteria of the EWMA control chart under both proposed algorithms is conducted.
机译:指数加权移动平均值(EWMA)控制图可用于检测过程平均值的微小变化。本文研究了EWMA控制图的多目标经济统计设计,并提出了两种进化算法,包括非主导排序遗传算法(NSGA-Ⅱ)和多目标遗传算法(MOGA),以确定最优的图表参数。 。本文使用的成本函数是Lorenzen和Vance成本函数。我们还使用了二次Taguchi损失函数来确定在控制内和控制外情况下生产不合格品的成本。通过使用马尔可夫链方法可以计算出处于控制状态和失控状态的平均行程长度值。通过数值算例比较了所提出算法在寻找多目标经济统计模型的帕累托最优解中的结果。最后,在两种算法下对EWMA控制图的经济性和统计标准进行敏感性分析。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号