OPTIMIZATION AND DECISION MAKING STAGES FOR ANALYSIS OF DUAL RESPONSE PROBLEM: MEDIAN-MAD, NSGA-II, TOPSIS

Abstract

The purpose of this study is to obtain a proper set of input variables for replicated response measured data set by applying dual response strategy in robust framework with multi-objective perspective. The replicated response measures were transformed to dual response by using robust statistics, median (MED) and median absolute deviation (MAD), instead of mean-standard deviation statistics which were very commonly used in many existing studies. A compromise solution of proposed robust dual response model was obtained via a multi-criteria decision making approach since the optimization was achieved in multi-objective point of view. In this study, well-known two methods, NSGA-II and TOPSIS, were preferred for optimization and decision making stages, respectively. Quality of printing ink data set was used an application from the literature. It is seen from the analysis results that the performance of the proposed robust dual response model was encouraging with the most satisfactory input settings.

Keywords

• Replicated response measures
• Dual response problem
• Robust statistics
• Multiobjective optimization
• Multi-criteria decision making

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