Graph Theory and Its Role in Vulnerability Evaluation of Infrastructure Networks

Seyed Ashkan Zarghami*, Indra Gunawan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


Infrastructure Networks (INs) have reached a level of complexity where conventional vulnerability analysis methods cannot fulfil the challenges for the management of this increasing complexity. There is, therefore, a need for a complementary approach through which the structural complexity and the level of interaction among the components are studied. In this context, researchers have increasingly looked into graph theory for help in understanding the structure, efficiency, and vulnerability of INs. The desire to employ the graph theory has resulted in the proliferation of a wide range of topological metrics. To gain a better appreciation for how various graph theory quantities have been used for vulnerability evaluation of INs, this chapter documents a variety of concepts from graph theory in one place and presents an overview of the application of graph theory in the field of INs. It also reviews the conceptions of the four widely used vulnerability-averse indicators of INs, which are reliability, resilience, robustness, and redundancy. The conventional graph theory methods are criticized on several grounds and the future evolution of graph theory tools is forecast.

Original languageEnglish
Title of host publication14th WCEAM Proceedings
EditorsAdolfo Crespo Márquez, Dragan Komljenovic, Joe Amadi-Echendu
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages11
ISBN (Print)9783030642273
Publication statusPublished - 2021
Externally publishedYes
Event14th World Congress on Engineering Asset Management, WCEAM 2019 - Singapore, Singapore
Duration: 28 Jul 201931 Jul 2019

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364


Conference14th World Congress on Engineering Asset Management, WCEAM 2019


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