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Duration: 2017-2020
Status: Ongoing
Project Contact: nazanin.vafaei@uninova.pt, rar@uninova.pt

Financing: FCT/MCTES

DynaNorm
Project Summary

Data normalization is essential for all kinds of decision-making problems because data has to be numerical and comparable to be aggregated into alternatives´ scores and then chose the best alternative (highest score). In multi-criteria decision-making (MCDM), normalization is the first step that converts criteria values into a common scale, thus enabling rating and ranking of alternatives.

Many multi-criteria decision-making methods use normalization techniques, which neither take into account the type of data nor if its normalization truly represents a mapping from source data to a representative scale. Although there are some attempts in the literature, to address the subject of normalization, there is still an important open question" which technique is more appropriate for usage on well-known MCDM methods?".

Hence, the main objective of this study is to develop an assessment evaluation framework for analyzing and recommending which are the best normalization techniques for multi-criteria decision methods. Also, we will prepare a taxonomy for normalization techniques and describe their advantages and disadvantages.

To validate and test the framework we will devise a validation strategy for comparing the normalization techniques and then explore the role of normalization techniques for two emergent topics in decision making, dynamic multi criteria decision making (DMCDM) and collaborative decision making, specifically related with problems of selection of suppliers, business partners, resources etc.






Apoio FCT – Fundação para a Ciência e a Tecnologia no âmbito da Unidade de Investigação CTS - Centro de Tecnologia e Sistemas, referência UID/EEA/00066/2013