Non-dominated sorting genetic algorithm (NSGA-II) approach to the multi-objective economic statistical design of variable sampling interval $T^2$ control charts

Authors : Asghar SEİF, Majide SADEGHİFAR

Pages : 203-214

View : 64 | Download : 12

Publication Date : 2015-02-01

Article Type : Research Paper

Abstract :$T^2$ control charts are used to primarily monitor the mean vector of quality characteristics of a process. Recent studies have shown that using variable sampling interval insert ignore into journalissuearticles values(VSI); schemes results in charts with more statistical power for detecting small to moderate shifts in the process mean vector. In this study, we have presented a multiple-objective economic statistical design of VSI $T^2$ control chart when the in-control process mean vector and process covariance matrix are unknown. Then we exert to find the Pareto-optimal designs in which the two objectives are minimized simultaneously by using the Non-dominated sorting genetic algorithm. Through an illustrative example, the advantages of the proposed approach is shown by providing a list of viable optimal solutions and graphical representations, thereby bolding the advantage of flexibility and adaptability.
Keywords : Hotellings T 2 control chart, Economic Statistical Design, NSGA II Algorithm, Multiple Objective Optimization, variable sampling interval VSI, scheme

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