El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr. (2010). Maximizing Temporary Housing Safety after Natural Disasters. Journal Of Infrastructure Systems, 16(2), 138 – 148.
View Publication
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.
View Publication
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.
View Publication
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.
View Publication
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.
View Publication
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.
View Publication
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.
View Publication
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).
View Publication
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
El-Anwar, Omar; Chen, Lei. (2014). Maximizing the Computational Efficiency of Temporary Housing Decision Support Following Disasters. Journal Of Computing In Civil Engineering, 28(1), 113 – 123.
View Publication
Abstract
Postdisaster temporary housing has long been a challenging problem because of its interlinked socioeconomic, political, and financial dimensions. A significant need for automated decision support was obvious to address this problem. Previous research achieved considerable advancements in developing optimization models that can quantify and optimize the impacts of temporary housing decisions on the socioeconomic welfare of displaced families and total public expenditures on temporary housing as well as other objectives. However, the computational complexity of these models hindered its practical use and adoption by emergency planners. This article analyzes the computational efficiency of the current implementation of the most advanced socioeconomic formulation of the temporary housing problem, which uses integer programming. Moreover, it presents the development of a customized variant of the Hungarian algorithm that has a superior computational performance while maintaining the highest quality of solutions. An application example is presented to demonstrate the unique capabilities of the new algorithm in solving large-scale problems.
Keywords
Decision Support Systems; Emergency Management; Integer Programming; Computational Efficiency; Temporary Housing Decision Support Following Disasters; Financial Dimensions; Political Dimensions; Socioeconomic Dimensions; Socioeconomic Welfare; Emergency Planners; Socioeconomic Formulation; Hungarian Algorithm; Multiobjective Optimization; Maeviz-hazturk; Housing; Computation; Disasters; Temporary Structures; Temporary Housing; Optimization; Disaster Management
Gatti, Umberto C.; El-anwar, Omar; Migliaccio, Giovanni C.; Lin, Ken-yu; Medina, Yvonne. (2014). Quantifying The Impacts Of Failures Of Departments Of Transportation Building Systems On Road System Users. Transportation Research Record, 2440, 85 – 93.
View Publication
Abstract
Because of the financial crisis of 2007 to 2008 and the subsequent economic downturn, funding for transportation agencies has been consistently reduced. This lack of funds prevents the building assets of transportation agencies from being efficiently maintained, so failures may occur that discontinue employees' operations and activities and affect transportation system users. Thus, to maximize the use of available funding, it is compelling to create innovative tools and techniques capable of estimating how potential failures can affect employees' activities and, eventually, transportation system users. Facility managers and decision makers could use such estimates to make decisions on maintenance of building assets that would minimize the risks of disruptions to employees and transportation system users. Among the capital assets of the Washington State Department of Transportation (DOT), transportation equipment fund (TEF) shops are crucial in ensuring timely and effective care and maintenance of the majority of state vehicles and equipment Therefore, any disruption of the operations of TEF shop facilities could significantly affect not only the Washington State DOT's vehicles and equipment maintenance but also the department's ability to fulfill its core mission. Given the importance of TEF shops, this exploratory case study investigates the failures that have occurred or are likely to occur in these facilities and employs discrete-event simulation to quantify the consequences of such failures on the shop activities and road users.
Keywords
Simulation