El-Anwar, Omar; Ye, Jin; Orabi, Wallied. (2016). Efficient Optimization of Post-Disaster Reconstruction of Transportation Networks. Journal Of Computing In Civil Engineering, 30(3).
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Abstract
Catastrophes, such as hurricanes, earthquakes, and tsunamis often cause large-scale damage to transportation systems. In the aftermath of these disasters, there is a present challenge to quickly analyze various reconstruction plans and assess their impacts on restoring transportation services. This paper presents a new methodology for optimizing post-disaster reconstruction plans for transportation networks with superior computational efficiency employing mixed-integer linear programming (MILP). The model is capable of optimizing transportation recovery projects prioritization and contractors assignment in order to simultaneously: (1)accelerate networks recovery; and (2)minimize public expenditures. The full methodology is presented in two companion publications, where the focus of this paper is to propose new methods for (1)decomposing traffic analysis; (2)assessing the traffic and cost performance of reconstruction plans; (3)reducing the massive solution search space; and (4)phasing the use of mixed-integer linear programming to optimize the problem. An illustrative example is presented throughout the paper to demonstrate the implementation phases. (C) 2015 American Society of Civil Engineers.
Keywords
Cost Reduction; Disasters; Emergency Management; Integer Programming; Linear Programming; Project Management; Public Finance; Search Problems; Town And Country Planning; Transportation; Solution Search Space Reduction; Cost Performance Assessment; Traffic Performance Assessment; Traffic Analysis; Public Expenditure Minimization; Network Recovery Acceleration; Contractor Assignment; Transportation Recovery Project Prioritization; Milp; Mixed-integer Linear Programming; Post-disaster Reconstruction Plan Optimization; Transportation Service Restoration; Reconstruction Plans; Transportation System Large-scale Damage; Tsunami; Earthquake; Hurricane; Catastrophe; Transportation Network; Post-disaster Reconstruction Optimization; Optimizing Resource Utilization; Natural Disasters; Housing Projects; Construction; Performance; Robustness; Recovery; Plans; Transportation Network Reconstruction; Post-disaster Recovery; Multi-objective Optimization; Computational Cost; Contractors Assignment; Search Space
El-Anwar, Omar; Ye, Jin; Orabi, Wallied. (2016). Innovative Linear Formulation for Transportation Reconstruction Planning. Journal Of Computing In Civil Engineering, 30(3).
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Abstract
Following disasters, the pace of restoring transportation networks can have a significant impact on economic and societal recovery. However, reconstruction and repair efforts are typically faced by budget constraints that require careful selection among competing contractors. This paper presents an innovative formulation to optimize this complex planning problem in order to maximize the rate of transportation network recovery while minimizing the associated reconstruction costs. This study first contributes to the body of knowledge by offering an effective and efficient means of identifying the optimal schedules for reconstruction projects and the optimal contractor assignments. This is achieved by solving the problem using a new mixed-integer linear programming model. However, there are four main formulation challenges to represent this problem using linear equations because of the need to use logical operators. As such, the second contribution of this study is in offering innovative solutions to overcome these formulation challenges, which are generalizable to other construction scheduling and planning problems. This paper is companion to another paper that describes a holistic optimization and traffic assessment methodology for post-disaster reconstruction planning for damaged transportation networks. (C) 2015 American Society of Civil Engineers.
Keywords
Integer Programming; Linear Programming; Transportation; Innovative Linear Formulation; Transportation Reconstruction Planning; Economic Recovery; Societal Recovery; Complex Planning Problem; Transportation Network Recovery; Mixed-integer Linear Programming Model; Traffic Assessment Methodology; Postdisaster Reconstruction Planning; Natural Disasters; Housing Projects; Construction; Optimization; Performance; Robustness; Earthquake; Efficiency; Recovery; Plans; Transportation Network Reconstruction; Post-disaster Recovery; Multi-objective Optimization; Mixed-integer Linear Programming; Contractors Assignment; Linear Formulation; Reconstruction Costs
Ibrahim, Amir; El-Anwar, Omar; Marzouk, Mohamed. (2018). Socioeconomic Impact Assessment of Highly Dense-Urban Construction Projects. Automation In Construction, 92, 230 – 241.
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Abstract
Dense-urban construction is reported to affect the social and economic welfare of surrounding residents and local businesses in various ways. However, research studies and practical methodologies aimed at assessing to what extent the choice of a construction plan that reduces such effect are very limited. The objective of this paper is to present the development of an automated assessment methodology to fill this research gap. To this end, two formulations are presented; one based on multi-attributed utility functions and the other based on monetary compensations for disruptions caused by construction operations. Both formulations assess the impacts of construction plans on (1) increased travel distance; (2) residents' relocation; (3) business loss; (4) business closure; and (5) noise inconvenience. The proposed automated methodology is implemented in five sequential phases and utilizes Geographical Information Systems (GIS) and Visual Basic Application (VBA). Using the proposed implementation, the two alternative formulations are applied to an infrastructure upgrading project in Cairo, Egypt that had five possible construction scenarios. While the two formulations resulted in the same preference order for the five scenarios, they exhibited different performance in terms of their (1) assessment relative values; (2) required input data and robustness; (3) ease of results interpretation; and (4) comprehensiveness and scalability. The developed framework shows promising results in terms of identifying and sorting the major root causes of the socioeconomic disruptions caused by dense urban construction. Results show that using the proposed methodology informs decision-making and planning at the early stages of a project, which in turn helps to reduce cost overruns and schedule delays.
Keywords
Construction Projects; Socioeconomics; Social Services; Construction Project Management; Building Design & Construction; Geographic Information Systems; Infrastructure (economics); Dense-urban Construction; Gis; Socioeconomic Assessment; Decision Making; Economics; Plant Shutdowns; Tourism Industry; Automated Assessment; Construction Operations; Construction Plan; Socio-economic Assessments; Socio-economic Impact Assessment; Urban Construction; Utility Functions; Visual Basic Application; Pavement Construction; Road; Sustainability; Behavior; Industry; Highway; Models; Choice
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
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