El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr. (2010). Maximizing Temporary Housing Safety after Natural Disasters. Journal Of Infrastructure Systems, 16(2), 138 – 148.
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Abstract
In the aftermath of large-scale natural disasters, emergency management organizations are expected to provide safe temporary housing for a large number of displaced families and to ensure that these housing arrangements are not located in hazardous areas. Potential postdisaster hazards can take many forms such as earthquake aftershocks, landslides, postearthquake soil liquefaction, flooding, hazardous material releases, etc. This paper presents the development of a multiobjective optimization methodology to support decision-makers in emergency management organizations in optimizing postdisaster temporary housing arrangements. The developed methodology incorporates (1) a safety model to measure and quantify temporary housing safety in the presence of multiple potential postdisaster hazards; (2) a cost model to minimize total public expenditures on temporary housing; and (3) a multiobjective optimization model to simultaneously maximize temporary housing safety and minimize public expenditures on temporary housing. An application to a large region is presented to illustrate the use of the models and demonstrate their capabilities in optimizing postdisaster temporary housing arrangements.
Keywords
Earthquake; Landslides; Optimization; Temporary Housing; Postdisaster Hazards; Housing Safety; Postdisaster Recovery
El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr. (2010). Minimization of Socioeconomic Disruption for Displaced Populations Following Disasters. Disasters, 34(3), 865 – 883.
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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.
Keywords
Natural Disasters; Hurricanes; Disaster Relief; Temporary Housing; Tsunamis; Multi-objective Optimization; Post-disaster Recovery; Social Welfare; Socioeconomic Disruption
El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr S. (2010). Maximizing the Sustainability of Integrated Housing Recovery Efforts. Journal Of Construction Engineering And Management, 136(7), 794 – 802.
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Abstract
The large-scale and catastrophic impacts of Hurricanes Katrina and Rita in 2005 challenged the efficacy of traditional postdisaster temporary housing methods. To address these challenges, the U.S. Congress appropriated $400 million to the Department of Homeland Security to support alternative housing pilot programs, which encourage innovative housing solutions that will facilitate sustainable and permanent affordable housing in addition to serving as temporary housing. Facilitating and maximizing the sustainability of postdisaster alternative housing is an important objective that has significant social, economic, and environmental impacts. This paper presents the development of a novel optimization model that is capable of (1) evaluating the sustainability of integrated housing recovery efforts under the alternative housing pilot program and (2) identifying the housing projects that maximize sustainability. An application example is analyzed to demonstrate the use of the developed model and its unique capabilities in maximizing the sustainability of integrated housing recovery efforts after natural disasters.
Keywords
Northridge Earthquake; United-states; Disasters; Optimization; Postdisaster Alternative Housing; Sustainability; Housing Recovery
Kandil, Amr; El-Rayes, Khaled; El-Anwar, Omar. (2010). Optimization Research: Enhancing the Robustness of Large-Scale Multiobjective Optimization in Construction. Journal Of Construction Engineering And Management, 136(1), 17 – 25.
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Abstract
Many construction planning problems require optimizing multiple and conflicting project objectives such as minimizing construction time and cost while maximizing safety, quality, and sustainability. To enable the optimization of these construction problems, a number of research studies focused on developing multiobjective optimization algorithms (MOAs). The robustness of these algorithms needs further research to ensure an efficient and effective optimization of large-scale real-life construction problems. This paper presents a review of current research efforts in the field of construction multiobjective optimization and two case studies that illustrate methods for enhancing the robustness of MOAs. The first case study utilizes a multiobjective genetic algorithm (MOGA) and an analytical optimization algorithm to optimize the planning of postdisaster temporary housing projects. The second case study utilizes a MOGA and parallel computing to optimize the planning of construction resource utilization in large-scale infrastructure projects. The paper also presents practical recommendations based on the main findings of the analyzed case studies to enhance the robustness of multiobjective optimization in construction engineering and management.
Keywords
Optimizing Resource Utilization; Trade-off; Highway Construction; Genetic Algorithms; Cost; Model; Network; Design; Colony; Optimization Models; Parallel Processing; Resource Management; Housing; Multiple Objective Analysis; Linear Analysis; Algorithms