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    Sustainable Disaster Recovery Decision-Making Support Tool: Integrating Economic Vulnerability into the Objective Functions of the Associated Stakeholders

    Source: Journal of Management in Engineering:;2017:;Volume ( 033 ):;issue: 002
    Author:
    Mohamed S. Eid
    ,
    Islam H. El-adaway
    DOI: 10.1061/(ASCE)ME.1943-5479.0000487
    Publisher: American Society of Civil Engineers
    Abstract: Natural disasters affect the built environment’s infrastructure and disturb the economic sector’s sustainability and welfare. This requires a disaster recovery decision support tool that capitalizes on the redevelopment opportunities to elevate societies to a more-sustainable and less-vulnerable status. As such, this paper presents an agent-based model approach that aims to meet the objectives of stakeholders while decreasing the community’s economic vulnerability. Accordingly, the proposed model adopts a five-step research methodology: (1) implementing a comprehensive economic vulnerability assessment tool; (2) developing the objective functions and learning algorithms of the associated stakeholders; (3) modeling the different attributes and potential strategies of the various stakeholders; (4) creating an interdependent agent based model that simulates the aforementioned information; and (5) interpreting and analyzing the results generated from the developed model. The model is developed and tested on the post-Katrina residential housing and economic financial recovery in three Mississippi coastal counties. The model proposed an evolving optimal budget distribution that decreased the economic vulnerability and increased the residential and economic recovery. Ultimately, the holistic framework utilized in this study lays down the foundation for a new generation of interdisciplinary managerial decision-making support tools.
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      Sustainable Disaster Recovery Decision-Making Support Tool: Integrating Economic Vulnerability into the Objective Functions of the Associated Stakeholders

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4238279
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    contributor authorMohamed S. Eid
    contributor authorIslam H. El-adaway
    date accessioned2017-12-16T09:05:07Z
    date available2017-12-16T09:05:07Z
    date issued2017
    identifier other%28ASCE%29ME.1943-5479.0000487.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4238279
    description abstractNatural disasters affect the built environment’s infrastructure and disturb the economic sector’s sustainability and welfare. This requires a disaster recovery decision support tool that capitalizes on the redevelopment opportunities to elevate societies to a more-sustainable and less-vulnerable status. As such, this paper presents an agent-based model approach that aims to meet the objectives of stakeholders while decreasing the community’s economic vulnerability. Accordingly, the proposed model adopts a five-step research methodology: (1) implementing a comprehensive economic vulnerability assessment tool; (2) developing the objective functions and learning algorithms of the associated stakeholders; (3) modeling the different attributes and potential strategies of the various stakeholders; (4) creating an interdependent agent based model that simulates the aforementioned information; and (5) interpreting and analyzing the results generated from the developed model. The model is developed and tested on the post-Katrina residential housing and economic financial recovery in three Mississippi coastal counties. The model proposed an evolving optimal budget distribution that decreased the economic vulnerability and increased the residential and economic recovery. Ultimately, the holistic framework utilized in this study lays down the foundation for a new generation of interdisciplinary managerial decision-making support tools.
    publisherAmerican Society of Civil Engineers
    titleSustainable Disaster Recovery Decision-Making Support Tool: Integrating Economic Vulnerability into the Objective Functions of the Associated Stakeholders
    typeJournal Paper
    journal volume33
    journal issue2
    journal titleJournal of Management in Engineering
    identifier doi10.1061/(ASCE)ME.1943-5479.0000487
    treeJournal of Management in Engineering:;2017:;Volume ( 033 ):;issue: 002
    contenttypeFulltext
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