A Methodology for Redesigning Networks by Using Markov Random Fields
Metadatos
Afficher la notice complèteAuteur
García Cabello, Julia; Castillo Valdivieso, Pedro Ángel; Aguilar-Luzón, María del Carmen; Chiclana Parrilla, Francisco; Herrera Viedma, EnriqueEditorial
MDPI
Materia
Universal decision making model Redesigning networks Markov random fields
Date
2021Referencia bibliográfica
García Cabello, J.; Castillo, P.A.; Aguilar-Luzon, M.-d.-C.; Chiclana, F.; Herrera-Viedma, E. A Methodology for Redesigning Networks by Using Markov Random Fields. Mathematics 2021, 9, 1389. https://doi.org/10.3390/math9121389
Résumé
Standard methodologies for redesigning physical networks rely on Geographic Information Systems (GIS), which strongly depend on local demographic specifications. The absence of a
universal definition of demography makes its use for cross-border purposes much more difficult.
This paper presents a Decision Making Model (DMM) for redesigning networks that works without
geographical constraints. There are multiple advantages of this approach: on one hand, it can be used
in any country of the world; on the other hand, the absence of geographical constraints widens the
application scope of our approach, meaning that it can be successfully implemented either in physical
(ATM networks) or non-physical networks such as in group decision making, social networks, ecommerce, e-governance and all fields in which user groups make decisions collectively. Case studies
involving both types of situations are conducted in order to illustrate the methodology. The model
has been designed under a data reduction strategy in order to improve application performance.