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An automated system for optimizing post-disaster temporary housing allocation
AbstractIn the aftermath of natural disasters, emergency management agencies need to provide adequate temporary housing solutions to accommodate the large number of displaced families. Disaster impact software systems, such as HAZUS-MH (FEMA) and MAEviz (MAE Center), enable emergency planners to estimate the expected displacement of families after natural disasters; however they lack the capability of providing temporary housing solutions. This paper presents the development of an automated system to support decision-makers in optimizing post-disaster temporary housing arrangements. The system has been integrated in MAEviz and provides the capability of optimizing a number of important objectives, including minimizing negative socioeconomic impacts, maximizing housing safety, minimizing negative environmental impacts, and minimizing public expenditures; in addition to other user-defined objectives. The system consists of three main models: (1) data collection; (2) automated optimization; and (3) output analysis and visualization. A large-scale application example is optimized to illustrate the use of the system and demonstrate its unique capabilities.
An automated system for optimizing post-disaster temporary housing allocation
AbstractIn the aftermath of natural disasters, emergency management agencies need to provide adequate temporary housing solutions to accommodate the large number of displaced families. Disaster impact software systems, such as HAZUS-MH (FEMA) and MAEviz (MAE Center), enable emergency planners to estimate the expected displacement of families after natural disasters; however they lack the capability of providing temporary housing solutions. This paper presents the development of an automated system to support decision-makers in optimizing post-disaster temporary housing arrangements. The system has been integrated in MAEviz and provides the capability of optimizing a number of important objectives, including minimizing negative socioeconomic impacts, maximizing housing safety, minimizing negative environmental impacts, and minimizing public expenditures; in addition to other user-defined objectives. The system consists of three main models: (1) data collection; (2) automated optimization; and (3) output analysis and visualization. A large-scale application example is optimized to illustrate the use of the system and demonstrate its unique capabilities.
An automated system for optimizing post-disaster temporary housing allocation
El-Anwar, Omar (author) / El-Rayes, Khaled (author) / Elnashai, Amr (author)
Automation in Construction ; 18 ; 983-993
2009-05-06
11 pages
Article (Journal)
Electronic Resource
English
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