Multiobjective Genetic Algorithm Approach to the Economic Statistical Design of Control Charts with an application to Xbar and S2 charts

Control charts are the primary tools of statistical process control. These charts may be designed by using a simple rule suggested by Shewhart, by a statistical criterion, an economic criterion or a joint economic-statistical criterion. Each method has its strengths and weaknesses. One weakness of the methods of design listed above is their lack of flexibility and adaptability, a primary objective of practical mathematical models. In this paper, we explore multi objective models as an alternative for the methods listed above. These provide a set of optimal solutions rather than a single optimal solution and thus allow the user to tailor their solution to the temporal imperative of a specific industrial situation. We present a solution to a well known industrial problem and compare optimal multi objective designs to economic designs, statistical designs, economic statistical designs and heuristic designs.