Normalization Techniques for Multi-Criteria Decision Making: Analytical Hierarchy Process Case Study - Technological Innovation for Cyber-Physical Systems Access content directly
Conference Papers Year : 2016

Normalization Techniques for Multi-Criteria Decision Making: Analytical Hierarchy Process Case Study

Abstract

Multi-Criteria Decision Making (MCDM) methods use normalization techniques to allow aggregation of criteria with numerical and comparable data. With the advent of Cyber Physical Systems, where big data is collected from heterogeneous sensors and other data sources, finding a suitable normalization technique is also a challenge to enable data fusion (integration). Therefore, data fusion and aggregation of criteria are similar processes of combining values either from criteria or from sensors to obtain a common score. In this study, our aim is to discuss metrics for assessing which are the most appropriate normalization techniques in decision problems, specifically for the Analytical Hierarchy Process (AHP) multi-criteria method. AHP uses a pairwise approach to evaluate the alternatives regarding a set of criteria and then fuses (aggregation) the evaluations to determine the final ratings (scores).
Fichier principal
Vignette du fichier
419233_1_En_26_Chapter.pdf (558.29 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01438251 , version 1 (17-01-2017)

Licence

Attribution

Identifiers

Cite

Nazanin Vafaei, Rita A. Ribeiro, Luis M. Camarinha-Matos. Normalization Techniques for Multi-Criteria Decision Making: Analytical Hierarchy Process Case Study. 7th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2016, Costa de Caparica, Portugal. pp.261-269, ⟨10.1007/978-3-319-31165-4_26⟩. ⟨hal-01438251⟩
331 View
6380 Download

Altmetric

Share

Gmail Facebook X LinkedIn More