Sustainable Disaster Recovery Framework: Reducing the Community Vulnerabilities throughout the Redevelopment Process
This paper presents a sustainable disaster recovery decision-making framework that meets the needs of the stakeholders in rebuilding damaged infrastructure while simultaneously decreasing the built environment's social, economic, and environmental vulnerabilities. Through utilizing agent-based modeling (ABM), the needs and preferences of the multi-sector stakeholders are integrated into the objectives of the modeled recovery agency. The proposed framework integrates well-established vulnerability indicators into the recovery agency's objective function to better guide the redevelopment process. Through utilizing an individual learning module, the model optimizes the post-disaster recovery strategies to decrease the vulnerabilities of the built environment throughout the recovery phase while increasing the overall recovery rate. The proposed model was tested on the post-Katrina recovery in Mississippi. In comparison to the actual recovery data and simulation scenarios, the proposed model provided higher recovery rates and elevated the built environment vulnerability status to achieve long-term sustainable disaster recovery.
M. S. Eid and I. H. El-adaway, "Sustainable Disaster Recovery Framework: Reducing the Community Vulnerabilities throughout the Redevelopment Process," Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019, pp. 498 - 506, American Society of Civil Engineers (ASCE), Jun 2019.
The definitive version is available at https://doi.org/10.1061/9780784482445.064
ASCE International Conference on Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience, i3CE 2019 (2019: Jun. 17-19, Atlanta, GA)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Autonomous agents; Computational methods; Decision making; Disasters; Recovery; Smart city, Agent-based model; Community vulnerability; Damaged infrastructure; Decision-making frameworks; Environmental vulnerability; Individual learning; Objective functions; Vulnerability indicators, Sustainable development
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 American Society of Civil Engineers (ASCE), All rights reserved.
01 Jun 2019