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International Conference on Dynamics of Disasters

DOD 2015 2016: Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights pp 191–205Cite as

Network Criticality and Network Complexity Indicators for the Assessment of Critical Infrastructures During Disasters

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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 185))

Abstract

Network criticality indicators, such as the Unified Network Performance Measure, provide powerful tools for interested entities who aim to assess those parts of the network, the closure of which would mostly affect its overall performance. The progress in complex networks analysis on the premises of graph theory allowed for advances on the identification of network characteristics and alternative sets of indicators for the evaluation of network performance. The aim of the present paper is to lay out the contribution of network analytics (in the form of complexity and criticality indicators) in disaster management, with the road network of the Peloponnese region, Greece, acting as a case study. Findings show that adopting interdisciplinary advances can provide useful insights to entities, responsible for the mitigation, preparedness, response, and reconstruction phases of disaster management and support them in the complex decision-making process.

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Author information

Authors and Affiliations

  1. Centre for Research and Technology Hellas – Hellenic Institute of Transport, 6th km Charilaou-Thermi Road, 57001, Thermi, Thessaloniki, Greece

    Evangelos Mitsakis, Josep Maria Salanova, Iraklis Stamos & Emmanouil Chaniotakis

Authors
  1. Evangelos Mitsakis
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  2. Josep Maria Salanova
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  3. Iraklis Stamos
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  4. Emmanouil Chaniotakis
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Corresponding author

Correspondence to Iraklis Stamos .

Editor information

Editors and Affiliations

  1. Department of Physics and Computer Science, Wilfrid Laurier University, Waterloo, Ontario, Canada

    Ilias S. Kotsireas

  2. Department of Operations and Information Management, University of Massachusetts, Amherst, Massachusetts, USA

    Anna Nagurney

  3. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

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© 2016 Springer International Publishing Switzerland

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Mitsakis, E., Salanova, J.M., Stamos, I., Chaniotakis, E. (2016). Network Criticality and Network Complexity Indicators for the Assessment of Critical Infrastructures During Disasters. In: Kotsireas, I., Nagurney, A., Pardalos, P. (eds) Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights. DOD 2015 2016. Springer Proceedings in Mathematics & Statistics, vol 185. Springer, Cham. https://doi.org/10.1007/978-3-319-43709-5_10

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