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ABSTRACT: In the aftermath of catastrophic natural disasters such as hurricanes, tsunamis and earthquakes, emergency management agencies come under intense pressure to provide temporary housing to address the large-scale displacement of the vulnerable population. Temporary housing is essential to enable displaced families to reestablish their normal daily activities until permanent housing solutions can be provided. Temporary housing decisions, however, have often been criticized for their failure to fulfil the socioeconomic needs of the displaced families within acceptable budgets. This paper presents the development of (1) socioeconomic disruption metrics that are capable of quantifying the socioeconomic impacts of temporary housing decisions on displaced populations; and (2) a robust multi-objective optimization model for temporary housing that is capable of simultaneously minimizing socioeconomic disruptions and public expenditures in an effective and efficient manner. A large-scale application example is optimized to illustrate the use of the model and demonstrate its capabilities ingenerating optimal plans for realistic temporary housing problems.
Disasters 03/2010; 34(3):865-83. · 0.69 Impact Factor
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ABSTRACT: Earthquakes and tsunamis often cause significant damages in civil infrastructure systems and housing units, leading to large-scale displacement of families. These displaced families need temporary housing arrangements, such as travel trailers and leased hotels, until permanent housing solutions are available. This article presents a multi-objective optimization model to support decision-makers in identifying optimal temporary housing arrangements for displaced families after natural disasters. The model is developed using weighted linear programming and is capable of optimizing four possibly conflicting objectives, namely: (1) minimizing negative socioeconomic impacts on displaced families; (2) maximizing safety of displaced families; (3) minimizing adverse environmental impacts; and (4) minimizing total public expenditures. The model was used to analyze and optimize a case study of temporary housing arrangements after the 1994 Northridge Earthquake. The analysis of this case study illustrates the potential use of the model by emergency management agencies and demonstrates its capabilities in optimizing temporary housing arrangements after earthquakes and other natural disasters.
Journal of Earthquake Engineering. 01/2008; 12(S2):81-91.
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ABSTRACT: Natural disasters, such as hurricanes, earthquakes, and tsunamis often cause large-scale destruction in residential areas. In the aftermath of these disasters, emergency management agencies need to urgently develop and implement a temporary housing plan that provides displaced families with satisfactory and safe accommodations. This paper presents the computational implementation of a newly developed multiobjective optimization model to support decision-makers in emergency management agencies in optimizing large-scale temporary housing arrangements. The model is capable of simultaneously minimizing 1 postdisaster social and economic disruptions suffered by displaced families; 2 temporary housing vulnerabilities to postdisaster hazards; 3 adverse environmental impacts on host communities; and 4 public expenditures on temporary housing. The model is implemented in four main phases and it incorporates four optimization modules to enable optimizing each of the aforementioned important objectives. A large-scale temporary housing application example is presented to demonstrate the unique capabilities of the model and illustrate the performed computations in each of the implementation phases.
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ABSTRACT: In 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.
Automation in Construction.
