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A Methodology for Redesigning Networks by Using Markov Random Fields

Author

Listed:
  • Julia García Cabello

    (Department of Applied Mathematics, University of Granada, 18071 Granada, Spain)

  • Pedro A. Castillo

    (Department of Computer Architecture and Computer Technology, University of Granada, 18071 Granada, Spain)

  • Maria-del-Carmen Aguilar-Luzon

    (Department of Social Psychology, University of Granada, 18071 Granada, Spain)

  • Francisco Chiclana

    (Institute of Artificial Intelligence, De Montfort University, Leicester LE1 9BH, UK)

  • Enrique Herrera-Viedma

    (Department of Computer Science and Artificial Intelligence, University of Granada, 18071 Granada, Spain)

Abstract

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, e-commerce, 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.

Suggested Citation

  • Julia García Cabello & Pedro A. Castillo & Maria-del-Carmen Aguilar-Luzon & Francisco Chiclana & Enrique Herrera-Viedma, 2021. "A Methodology for Redesigning Networks by Using Markov Random Fields," Mathematics, MDPI, vol. 9(12), pages 1-13, June.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:12:p:1389-:d:575263
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    References listed on IDEAS

    as
    1. García Cabello, Julia, 2017. "The future of branch cash holdings management is here: New Markov chains," European Journal of Operational Research, Elsevier, vol. 259(2), pages 789-799.
    2. Yilun Shang, 2020. "Multi-Hop Generalized Core Percolation On Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 1-15, March.
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