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
El-Anwar, Omar. (2013). Advancing Optimization of Hybrid Housing Development Plans Following Disasters: Achieving Computational Robustness, Effectiveness, and Efficiency. Journal Of Computing In Civil Engineering, 27(4), 358 – 369.
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Abstract
Following disasters, displaced families often face significant challenges to move from temporary to permanent housing. The Federal Emergency Management Agency is exploring alternative housing pilot programs to evaluate the possibility of providing quickly deployable, affordable housing that can serve both as temporary and permanent housing. Because of the complexities and costs associated with these programs, it is impractical to assume that accelerated permanent housing can fully replace the need for traditional temporary housing, especially in cases of large-scale displacements. A novel methodology was developed to evaluate the socioeconomic benefits of candidate configurations of hybrid housing plans, which incorporates both temporary and accelerated permanent housing developments. This paper presents the computational implementation and performance analysis of this novel methodology to offer a practical decision-support tool to emergency planners. To this end, genetic algorithms and integer-programming optimization models are formulated, and their performances are analyzed based on their effectiveness, efficiency, and robustness. In lieu of developing the integer-programming model, the paper also presents a linear formulation that overcomes the need to use logical operations to model fixed and variable cost components for developing housing projects. Results show the superior performance of integer programming, whereas genetic algorithms offer higher modeling flexibility.
Keywords
Decision Support Systems; Emergency Management; Genetic Algorithms; Integer Programming; Advancing Optimization; Hybrid Housing Development Plans Following Disasters; Achieving Computational Robustness; Achieving Computational Effectiveness; Achieving Computational Efficiency; Federal Emergency Management Agency; Housing Pilot Programs; Temporary Housing; Permanent Housing Developments; Decision-support Tool; Emergency Planners; Integer-programming Optimization Models; Logical Operations; Optimization; Disasters; Housing; Social Factors; Economic Factors; Computation; Hybrid Methods; Disaster Recovery; Accelerated Permanent Housing; Socioeconomic Welfare; Robustness; Effectiveness; Computational Efficiency; 0
El-Anwar, Omar. (2013). Maximising the Net Social Benefit of the Construction of Post-Disaster Alternative Housing Projects. Disasters, 37(3), 489 – 515.
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Abstract
The widespread destruction that follows large-scale natural disasters, such as Hurricane Katrina in August 2005, challenges the efficacy of traditional temporary housing methods in providing adequate solutions to housing needs. Recognising these housing challenges, the Congress of the United States allocated, in 2006, USD 400 million to the Department of Homeland Security to support Alternative Housing Pilot Programs, which are intended to explore the possibilities of providing permanent and affordable housing to displaced families instead of traditional temporary housing. This paper presents a new methodology and optimisation model to identify the optimal configurations of post-shelter housing arrangements to maximise the overall net socioeconomic benefit. The model is capable of quantifying and optimising the impacts of substituting temporary housing with alternative housing on the social and economic welfare of displaced families as well as the required additional costs of doing so. An application example is presented to illustrate the use of the model and its capabilities.
Keywords
Public Housing; Temporary Housing; Hurricane Katrina, 2005; Natural Disasters; Socioeconomic Factors; Mathematical Models; Mathematical Optimization; United States; Alternative Housing Pilot Programs; Optimisation; Socioeconomic Benefit; Disasters