A Methodology for Redesigning Networks by Using Markov Random Fields
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AuthorGarcía Cabello, Julia; Castillo Valdivieso, Pedro Ángel; Aguilar-Luzón, María del Carmen; Chiclana Parrilla, Francisco; Herrera Viedma, Enrique
Universal decision making modelRedesigning networksMarkov random fields
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
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.