Inoperability Input-Output Model for Interdependent Infrastructure Sectors. I: Theory and Methodology

By Yacov Y. Haimes, B. Horowitz, J. Lambert, Joost R. Santos, Chenyang Lian, K. Crowther. 2005

420 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/be42a175c3f58c39e6f3234d83bdd6b378a012f4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Y. Okuyama
2. Joost R. Santos
3. Zhenghua Wang
4. Adam Rose
5. Ouyang Min
6. Stéphane Hallegatte
7. Rio Yonson
8. Ilan Noy

In Control and Systems Engineering

1. Ouyang Min
2. Zhenghua Wang

In Statistics and Probability

1. Y. Okuyama
2. Adam Rose
3. Ouyang Min
4. Joost R. Santos
5. Zhenghua Wang

Citations in the corpus

• Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis (2015, methodology): “Based on the initial perturbations of sectors caused by the event and on the estimated recovery times, the adapted model could calculate the inoperabilities and economic losses of interdependent sectors during the recovery period [26-27].”
• DISASTER IMPACT AND INPUT–OUTPUT ANALYSIS (2014, background): “Their extension starts from the Dynamic Inoperability Input–Output Modeling, proposed by Haimes et al. (2005), and proposes alternative resilience formulations to create more flexible disaster recovery paths.”
• Economic Resilience to Disasters (2009, background): “* Haimes et al. (2005a) combined engineering and economic considerations in a useful disaster impact and policy framework--the Inoperability Input-Output Model.”
• Economic resilience to natural and man-made disasters: Multidisciplinary origins and contextual dimensions (2007, background): “In fact, they emphasize how ‘‘hardening’’ and other risk mitigation efforts increase resilience during recovery (Haimes et al., 2005a, p. 74) and otherwise neglect post-disaster considerations.”