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
El-Anwar, Omar; Chen, Lei. (2013). Computing a Displacement Distance Equivalent to Optimize Plans for Postdisaster Temporary Housing Projects. Journal Of Construction Engineering And Management, 139(2), 174 – 184.
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Abstract
Residence in temporary housing is a critical period for the social, economic, and psychological recovery of displaced families following disasters. Temporary housing locations define the displacement distance between families and their essential needs. The objective of this paper is to develop a novel methodology to capture the specific proximity needs and preferences of displaced families. This paper proposes a displacement distance equivalent as an objective metric to evaluate the performance of temporary housing locations in meeting the needs of displaced families. Moreover, the paper describes the development of an integer programming optimization model capable of optimizing temporary housing assignments to minimize total displacement distance equivalent while meeting budget constraints. The main contribution of this paper to the body of knowledge is in transforming the purpose of temporary housing programs from offering general accommodation to providing customized housing solutions tailored to the individual proximity needs of each household using the proposed displacement metric. In addition, the proposed optimization model enables decision makers to set budget constraints to ensure the economic feasibility of identified temporary housing solutions. DOI: 10.1061/(ASCE)CO. 1943-7862.0000601. (C) 2013 American Society of Civil Engineers.
Keywords
Disasters; Emergency Management; Integer Programming; Social Sciences; Displaced Families; Customized Housing Solutions; Decision Makers; Displacement Metric; Budget Constraints; Integer Programming Optimization Model; Objective Metric; Temporary Housing Locations; Post-disaster Temporary Housing Projects; Displacement Distance Equivalent Computation; Multiobjective Optimization; Optimization; Temporary Housing; Disaster Recovery; Displacement Distance; Housing Sites
El-Anwar, Omar; Aziz, Tamer Abdel. (2014). Integrated Urban-Construction Planning Framework for Slum Upgrading Projects. Journal Of Construction Engineering And Management, 140(4).
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Abstract
Slums are areas of population concentrations developed in the absence of physical planning and lack access to life essentials. Slums represent major national challenges in countries where they exist, especially developing countries. Various intervention strategies can be adopted to upgrade and/or replace slums, but are often faced with serious construction challenges, such as lack of access to sites and poor terrain conditions. Moreover, during the execution of slum upgrading projects, resident families can experience significant social and economic disruptions. The objective of this paper is present an integrated urban-construction planning framework for slum upgrading projects. This framework incorporates participatory upgrading and is designed to achieve three important objectives, including (1)maximizing the benefits of slum upgrading projects by identifying and accelerating the delivery of urgent projects; (2)providing more accurate and practical estimates of upgrading projects costs and timelines, which enables controlling and minimizing the total projects costs and durations; and (3)minimizing the social and economic disruptions for resident families during construction. An illustrative example is presented to demonstrate the potential of the proposed framework and its core multiobjective optimization process.
Keywords
Construction; Industrial Economics; Optimisation; Planning; Project Management; Social Sciences; Integrated Urban-construction Planning Framework; Slum Upgrading Projects; Physical Planning; Intervention Strategies; Construction Challenges; Economic Disruptions; Social Disruptions; Urgent Projects Delivery; Project Costs; Multiobjective Optimization Process; Logistics; Constructability; Optimization; Design; Build; Urban Areas; Slums Upgrading; Logistics Planning; Multi-objective Optimization; Integrated Design-build; Project Planning And Design