Informatica

This paper examines ranking reversal (RR) in Multiple Criteria Decision Making (MCDM) using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Through a mathematical analysis of min-max and max normalization techniques and distance metrics (Euclidean, Manhattan, and Chebyshev), the study explores their impact on RR, particularly when new, high-performing alternatives are introduced. This research provides insight into the causes of RR, offering a framework that clarifies when and why RR occurs. The findings help decision-makers select appropriate techniques, promoting more consistent and reliable outcomes in real-world MCDM applications.

In this study, we evaluated the effects of the normalization procedures on decision outcomes of a given MADM method. For this aim, using the weights of a number of attributes calculated from FAHP method, we applied TOPSIS method to evaluate the financial performances of 13 Turkish deposit banks. In doing this, we used the most popular four normalization procedures. Our study revealed that vector normalization procedure, which is mostly used in the TOPSIS method by default, generated the most consistent results. Among the linear normalization procedures, max-min and max methods appeared as the possible alternatives to the vector normalization procedure.

This paper presents a bimodal biometric verification system based on the fusion of palmprint and face features at the matching-score level. The system combines a new approach to palmprint principal lines recognition based on hypotheses generation and evaluation and the well-known eigenfaces approach for face recognition. The experiments with different matching-score normalization techniques have been performed in order to improve the performance of the fusion at the matching-score level. A “chimerical” database consisting of 1488 palmprint and face image pairs of 241 persons was used in the system design (440 image pairs of 110 persons) and testing (1048 image pairs of 131 persons). The experimental results show that system performance is significantly improved over unimodal subsystems.