A simulation based comparative study of normalization procedures in multiattribute decision making

Normalization procedures are required in multiattribute decision making (MADM) to transform performance ratings with different data measurement units in a decision matrix into a compatible unit. MADM methods generally use one particular normalization procedure without considering the suitability of other available procedures. This study compares four commonly known normalization procedures in terms of their ranking consistency and overall preference value consistency when used with the most widely used simple additive weight method. To achieve this, new performance measure indices are introduced and new simulation settings are devised for dealing with various measurement settings. A wide range of MADM problems with various measurement scales are generated by simulation for the comparison study. The experiment result shows that vector normalization and linear scale transformation (the max method) outperforms other normalization procedures when used with SAW.

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