Optimization of univariate and multivariate exponentially weighted moving-average control charts using genetic algorithms

Optimization of univariate and multivariate exponentially weighted moving-average control charts using genetic algorithms

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Article ID: iaor2005404
Country: United Kingdom
Volume: 31
Issue: 9
Start Page Number: 1437
End Page Number: 1454
Publication Date: Aug 2004
Journal: Computers and Operations Research
Authors: ,
Keywords: heuristics, optimization
Abstract:

Exponentially weighted moving-average (EWMA) and multivariate EWMA (MEWMA) process control charts can be applied to detect small changes in statistical process control efficiently. This paper presents a software program developed in Windows environment for the optimal design of the EWMA and MEWMA chart parameters, to protect the process in the case of shifts of given size. Optimization has been done using genetic algorithms.

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