Wallied Orabi

Optimizing Postdisaster Reconstruction Planning for Damaged Transportation Networks

The limited availability of reconstruction resources is one of the main challenges that often confront postdisaster recovery of damaged transportation networks. This requires an effective and efficient deployment and utilization of these limited resources in order to minimize both the performance loss of the damaged transportation network and the reconstruction costs. This paper presents the development of a robust model for planning postdisaster reconstruction efforts that is capable of: (1) optimizing the allocation of limited reconstruction resources to competing recovery projects; (2) assessing and quantifying the overall functional loss of damaged transportation networks during the recovery efforts; (3) evaluating the impact of limited availability of resources on the reconstruction costs; and (4) minimizing the performance loss of transportation networks and reconstruction costs. The model utilizes the user equilibrium algorithm to enable the assessment of the transportation network performance losses and a multiobjective genetic algorithm to enable the generation of optimal tradeoffs between the two recovery planning objectives. An application example is analyzed to demonstrate the use and capabilities of the recovery planning model.

Optimizing Resource Utilization during the Recovery of Civil Infrastructure Systems

Postdisaster recovery efforts of damaged civil infrastructure systems need to be optimized in order to alleviate the adverse impacts of natural disasters on local societies and economies. This paper presents an innovative framework that integrates two newly developed models for resource utilization and multiobjective optimization that are designed to optimize these recovery efforts. The developed models provide new and unique capabilities, including (1) allocating limited reconstruction resources to competing recovery projects, (2) estimating the reconstruction duration and cost associated with implementing specific recovery plans, and (3) generating optimal trade-offs between minimizing the reconstruction duration and cost. An application example is analyzed to evaluate the performance of the developed models and demonstrate their capabilities in identifying a wide spectrum of optimal reconstruction plans, where each provides a unique and nondominated trade-off between minimizing the recovery duration and cost. This allows decision makers in emergency management agencies to select and implement reconstruction plans that address various societal and economical needs in the aftermath of natural disasters.

Optimizing the rehabilitation efforts of aging transportation networks

AbstractMajor roads and bridges in the United States are aging and deteriorating, which is causing significant human and economic losses. The required investments to rehabilitate these transportation networks exceed available funds and budgets. The rehabilitation efforts of these aging networks, therefore, need to be optimized to maximize their net benefits and reduce the effect of construction works on the traveling public. This paper presents the development of an innovative model aimed at aiding decision makers in planning and optimizing highway rehabilitation programs. This model provides new and unique capabilities, which include: allocating limited financial resources to competing highway rehabilitation projects, measuring the effect of rehabilitation efforts on network performance and road user savings, analyzing the expected benefits and costs of rehabilitation programs, and generating optimal tradeoffs between maximizing rehabilitation benefits and minimizing network service disruption using a ge...

Minimizing Greenhouse Gas Emissions from Construction Activities and Processes

The construction industry has a significant environmental footprint, especially in terms of greenhouse gas emissions and energy consumption. Substantial amounts of greenhouse gasses and non-greenhouse gasses that have an indirect radiative effect are emitted from construction activities and processes and during production, installation, maintenance, and end-of-life disposal of construction materials. These emissions can be controlled and minimized by optimizing the utilization of construction resources. This includes the optimal utilization of the available construction crews and materials in such a way that reduces greenhouse gas emissions while minimizing construction cost and duration. Therefore, this paper presents the development of a building construction planning model that is capable of minimizing greenhouse gas emissions, construction cost, and construction duration, simultaneously. The model is implemented in three main steps: (1) analyzing the impact of construction activities and processes on global warming potential (GWP); (2) evaluating the impact of these activities and processes on construction cost and duration; and (3) optimizing the utilization of construction resources in order to facilitate the selection and implementation of the construction methods that reduces the GWP while keeping construction cost and duration to a minimum. An application example is analyzed to illustrate the use of the developed model and examine the relationships between all three planning objectives. The analysis of the application example demonstrated the capabilities of the developed model in controlling the global warming impacts from construction activities and processes. Furthermore, the examination of the relationships between GWP and construction duration and cost can help designers and construction professionals in making environmentallyconscious yet cost-effective decisions during building design and construction phases.

PLANNING POST-DISASTER RECONSTRUCTION EFFORTS OF DAMAGED TRANSPORTATION NETWORKS

Planning the reconstruction efforts of damaged transportation networks in the aftermath of natural disasters is a challenging task due to the limited availability of construction resources. The utilization of these limited resources can have a significant impact on the societal needs of minimizing the reconstruction costs and the performance loss of the damaged transportation network. These resources therefore need to be deployed and utilized in an effective and efficient manner that accomplishes these two critical objectives. This paper presents the development of a planning model for post-disaster reconstruction efforts for damaged transportation networks. The model is developed in four stages: (1) allocating the available reconstruction resources to competing recovery projects; (2) estimating the reconstruction costs; (3) measuring the performance loss during the recovery period; and (4) optimizing the reconstruction efforts to minimize reconstruction costs and performance loss. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in planning post-disaster reconstruction efforts.

Innovative Linear Formulation for Transportation Reconstruction Planning

AbstractFollowing 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...

Optimizing environmental sustainability and public benefits of transportation network programs

Transportation is among the highest energy-consuming economy sectors. Therefore, new national priorities and laws passed in the United States in an effort to control the environmental impacts of highway rehabilitation efforts. This created new challenges to planners and decision makers in transportation agencies to optimize, under budget constraints, rehabilitation efforts of aging networks in order to maximize net public benefits while minimizing network energy consumption. This mandates a substantial change in existing ad-hoc and need-based decision-making practices in order to add new criteria to evaluate and measure network energy consumption. Accordingly, this paper presents a new model for planning highway rehabilitation efforts that is capable of identifying near optimal program(s) in terms of maximizing net public benefits while minimizing energy consumption of transportation networks. The new model is designed to: (1) evaluating and measuring the impact of decision making in highway rehabilitation programs on network energy consumption; (2) evaluating the impact of rehabilitation decisions on the cost of travel delays due to highway construction work; (3) estimating the expected savings in road user costs due to the completed rehabilitation efforts; (4) estimating the lifecycle public costs and benefits associated with highway rehabilitation decisions; and (5) optimizing rehabilitation decisions in order to search for and identify the highway construction program(s) that simultaneously maximize public benefits and minimize energy consumption under budget constraints. An application example for a transportation network in South Florida is analyzed to demonstrate the model capabilities and examine the relationship between lifecycle net public benefits and total network energy consumption. The analysis of the application example showed that there is a trade-off between the expected net public benefits and network energy consumption. The new model should prove useful to transportation agencies in identifying rehabilitation program(s) that satisfy public expectations while minimizing energy consumption in transportation networks.

Optimizing Highway Rehabilitation Decisions to Minimize Fuel Consumption in Transportation Networks

Rehabilitation of aging roads has a significant impact on pavement performance and hence vehicle fuel consumption in transportation networks. Therefore, thorough analysis and evaluation of highway rehabilitation decisions and strategies can result in significant savings in fuel consumption in transportation networks. However, it is a challenging task to optimize highway rehabilitation decisions in order to minimize network fuel consumption and maximize net public benefits while satisfying several constraints such as limited funding and targets established for overall pavement performance. This paper presents a new model developed for optimizing and planning highway rehabilitation efforts that is designed to: (1) identify candidate rehabilitation treatment alternatives to deteriorating pavement; (2) evaluate and forecast the impact of implementing such treatments on pavement performance; (3) estimate total network fuel consumption as a result of selected rehabilitation decisions; (4) evaluate the cost of travel delay due to construction operations; (5) measure the impact of rehabilitation decision making on the expected savings in road user costs; and (6) optimize rehabilitation decisions to identify highway program(s) that simultaneously minimize network fuel consumption while maximizing net public benefits. The model is applied to a hypothetical example of an aging transportation network example in South Florida and was capable of generating optimal tradeoffs between public benefits and fuel consumption. This model should prove useful to state highway agencies in identifying and implementing cost-effective and energy-efficient highway rehabilitation programs.

Estimating Fuel Consumption from Highway-Rehabilitation Program Implementation on Transportation Networks

Reducing fuel consumption on roadway networks can have a huge impact on the nation’s economy and environment. Existing ad-hoc transportation planning efforts that allocate limited funding on need-based criteria are insufficient for providing a significant reduction in fuel consumption. Therefore, there is an urgent need for new research to analyze the impact of planning effort on fuel consumption to support transportation’s decision making. This paper presents the development of a new model for estimating fuel consumption in transportation networks under budget constraints by taking into consideration the effect of pavement deterioration on fuel consumption. The model is composed of three main modules to (1) estimate vehicle fuel consumption of transportation networks; (2) allocate limited funding to competing highway rehabilitation projects; and (3) evaluate the impact of pavement roughness and deterioration on fuel consumption. An application example is analyzed to evaluate the developed model and illustrate capabilities of the model. The application result demonstrates the significant impact of highway rehabilitation planning on fuel consumption on roadway networks. This study should prove useful to planners and decision makers in evaluating the impact of highway rehabilitation efforts on fuel consumption.

Efficient Analysis and Optimization of Reconstruction Plans for Damaged Transportation Networks Following Disasters

Planning for post-disaster reconstruction of damaged transportation networks is a complex and computationally expensive effort. Decision makers need to prioritize the use of limited resources to maximize societal benefit through accelerated traffic services restoration, which involves evaluating numerous recovery scenarios. This paper presents a new model that enables efficient analysis and optimization of the post-disaster reconstruction of transportation networks that is capable of identifying optimal reconstruction plans using reasonable computational overhead. The model employs a number of search space reduction techniques using mixed linear-integer programming and goal programming-inspired approaches in order to explore the large space of possible alternative solutions. Each of these solutions is comprised of a set of interdependent variables, including (1) contractors selection; and (2) the start dates of reconstruction projects and their constituent work packages. An application example is used to demonstrate the new models superior computational performance compared to recent research developments.