A new soft computing approach for analyzing the influential relationships of critical infrastructures

Huai-Wei Lo, James J.H. Liou, Chun-Nen Huang, Yen-Ching Chuang and Gwo-Hshiung Tzeng

International Journal of Critical Infrastructure Protection, 2020, vol. 28, issue C

Abstract: Approaches to risk assessment for the protection and management of critical infrastructures must continue to evolve to address uncertainty and hazards that may be encountered in the future. Extreme climate change and accidents arising from human activity increasingly threaten critical infrastructures. There are two vital issues to consider when protecting critical infrastructures: their interdependencies and priorities. We propose a novel hybrid multi-criteria decision-making model for uncertain environments, derived from the opinions of multiple experts, capable of building an influence network relationship and analyzing the influence and importance of critical infrastructures. The proposed model overcomes the problems caused by the diverse of opinions of experts arising from inherent conflicts due to their different backgrounds. The proposed model maps out the interdependencies and priorities among critical infrastructures in a complex system. The model developed in this study can support decision-makers and regulatory agencies when deciding upon appropriate protection plans. The effectiveness of the proposed model is demonstrated by conducting a case study involving Taiwan. The results indicate that the proposed model can effectively assist managers to evaluate the influential relationships among critical infrastructures and identify those which are most critical.

Keywords: Critical infrastructure; MCDM; Rough number; Fuzzy theory; DANP; Soft computing (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ijocip:v:28:y:2020:i:c:s1874548219301337

DOI: 10.1016/j.ijcip.2019.100336

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