EXPANDING DATA NORMALIZATION METHOD TO CODAS METHOD FOR MULTI-CRITERIA DECISION MAKING

Abstract

Data normalization is the conversion of quantities of different dimensions to the same dimensionless form, which is required in multicriteria decision making (MCDM). The choice of data normalization method has a direct influence on the decision-making results. This study presents the combination of CODAS (COmbinative Distance-based ASsessment) method with six different data normalization methods including Linear normalization, Max - Min linear normalization, Vector normalization, Sum linear normalization, Logarithmic normalization, Max linear normalization . These six combinations have been applied in turn in three different examples. The number of alternatives, the number of criteria, and the method of the weight calculation in these examples are also different. From the results it was reported that only the combination of CODAS and Logarithmic normalization was not suitable. The combination of CODAS with some other data normalization methods not mentioned in this study and it needs to be done in the near future. This task was covered in the last part of this paper.

Keywords

• mcdm
• codas method
• data normalization
• linear normalization
• max - min linear normalization
• vector normalization