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

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

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.

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  • Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching & Tzeng, Gwo-Hshiung, 2020. "A new soft computing approach for analyzing the influential relationships of critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
    • Handle: RePEc:eee:ijocip:v:28:y:2020:i:c:s1874548219301337
    DOI: 10.1016/j.ijcip.2019.100336
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    2. Fabio De Felice & Ilaria Baffo & Antonella Petrillo, 2022. "Critical Infrastructures Overview: Past, Present and Future," Sustainability, MDPI, vol. 14(4), pages 1-20, February.
    3. Molinos-Senante, María & Chamorro, Alondra & Contreras, Marta & Echaveguren, Tomas, 2023. "Natural hazard risk management in the Chilean drinking water industry: Diagnosis and recommendations," Utilities Policy, Elsevier, vol. 82(C).
    4. Jen-Jen Yang & Huai-Wei Lo & Chen-Shen Chao & Chih-Chien Shen & Chin-Cheng Yang, 2020. "Establishing a Sustainable Sports Tourism Evaluation Framework with a Hybrid Multi-Criteria Decision-Making Model to Explore Potential Sports Tourism Attractions in Taiwan," Sustainability, MDPI, vol. 12(4), pages 1-20, February.
    5. Chi-Yo Huang & Chia-Lee Yang & Yi-Hao Hsiao, 2021. "A Novel Framework for Mining Social Media Data Based on Text Mining, Topic Modeling, Random Forest, and DANP Methods," Mathematics, MDPI, vol. 9(17), pages 1-21, August.
    6. Bhandari, Pratik & Creighton, Douglas & Gong, Jinzhe & Boyle, Carol & Law, Kris M.Y., 2023. "Evolution of cyber-physical-human water systems: Challenges and gaps," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    7. Tien-Li Chen & Chin-Chuan Chen & Yen-Ching Chuang & James J. H. Liou, 2020. "A Hybrid MADM Model for Product Design Evaluation and Improvement," Sustainability, MDPI, vol. 12(17), pages 1-22, August.

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