Development of data normalization methods for multi-criteria decision making: applying for MARCOS method

Abstract

The purpose of the data normalization is to transfer the quantities with different dimensions to the same dimensionless form. The multi-criteria decision-making (MCDM) methods that require identifying the weight for each criterion, so the data normalization should be performed. In this study, five distinct data normalization methods were used in combination with a multi-criteria decision-making method (MARCOS method). All five of these data normalization methods were performed in combining with the MARCOS method and applied in three different cases. The number of solutions and the criteria in each case were different. Two different weighting methods were also used in each situation. After defining the most suitable data normalization methods in combining with the MARCOS method, this study proposed two new data normalization methods. The results show that solution rank is likely stable. The works in the future were mentioned in the last section of this article as well.