Abstract
The process of re-structuring physical networks is often based on local demographics. However, there are major variations across countries when defining demographics according to “local” parameters, which hinders the export of methodologies based on local specifications. This paper presents a universal decision making model for re-structuring networks aimed at working on a global basis since local parameters has been replaced by “internationally accepted” notions thereby allowing cross-border correlations. This a first step towards the globalization of demographic parameters which would also be fruitful in other disciplines where demographics play a role.
Importantly, the model variables can be replaced/expanded as needed thereby providing a decision making tool that can be applied to a wide range of contexts.
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Acknowledgments
This study was funded by FEDER funds under grant TIN2016-75850-R. Moreover, financial support from Proyectos de Excelencia 2012 Junta de Andalucía “Mecanismos de resolución de crisis: cambios en el sistema financiero y efectos en la economía real” (P12-SEJ-2463) is gratefully acknowledged.
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Cabello, J.G., Herrera-Viedma, E. (2018). A Universal Decision Making Model for Restructuring Networks Based on Markov Random Fields. In: Herrera, F., et al. Advances in Artificial Intelligence. CAEPIA 2018. Lecture Notes in Computer Science(), vol 11160. Springer, Cham. https://doi.org/10.1007/978-3-030-00374-6_16
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DOI: https://doi.org/10.1007/978-3-030-00374-6_16
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