Original Article

A comparative evaluation of data normalization techniques using different metrics: practical application to a MCDM method

¹ Faculty of Mechanical Engineering, Hanoi University of Industry, Hanoi, Vietnam
² Osmaniye Korkut Ata University, Faculty of Business and Administrative Sciences, Osmaniye, Türkiye

^* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 16 February 2025
Accepted: 23 June 2025

Abstract

Data normalization plays a crucial role in determining the ranking of alternatives in multi-criteria decision-making (MCDM) problems. The aim of this study is to investigate the effectiveness of various normalization techniques for the multiple criteria ranking by alternative trace (MCRAT) method. The suitability of nine distinct normalization techniques from literature for the MCRAT method has been assessed through four different case studies. The criteria weights were determined using the symmetry point of criterion (SPC) method. To evaluate the effectiveness of the normalization techniques, a five-step process involving Minkowski metrics was applied. The results indicate that the double normalization technique is the most appropriate technique for the MCRAT method. This finding suggests that double normalization is an effective approach for improving the reliability of the MCRAT method's results. This study fills an important gap in the field by providing an in-depth analysis of the effects of different normalization procedures on MCRAT applications. It is believed that the findings of this study will assist decision-makers in making more robust and efficient decisions by considering the potential impacts of various normalization techniques.