Browsing by Author "Damnjanovic, Ivan"
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Item A Tool for the Analysis of Real Options in Sustainability Improvement Projects(2012-10-19) Boonchanta, NaponThe major challenges in sustainable implementation are the financial issue and uncertainties. The traditional financial budgeting approach that is commonly used to evaluate sustainable projects normally neglects future decisions that might need to be made over the course of a project. The real options approach has been suggested as a tool for strategic decision making because it can provide flexibility which can increase the project value. Researchers have been trying to identify the potential of the real options approach, and provide the frameworks for a real options evaluation and flexible strategy in sustainability improvement. However, some important variables and financial impacts explanation of real options are missing. Models can be improved to show the variation of possible project values along with its behavior. This work aims to improve the real options model in sustainable projects to provide understanding about the financial impacts of flexible strategy to sustainable improvement projects and to be used as a tool to assist decision making. The results showed that real options can have a positive financial impact to the project. The extension of this model can assist the analysis and development of decision policies.Item Accounting for the effects of rehabilitation actions on the reliability of flexible pavements: performance modeling and optimization(2009-05-15) Deshpande, Vighnesh PrakashA performance model and a reliability-based optimization model for flexible pavements that accounts for the effects of rehabilitation actions are developed. The developed performance model can be effectively implemented in all the applications that require the reliability (performance) of pavements, before and after the rehabilitation actions. The response surface methodology in conjunction with Monte Carlo simulation is used to evaluate pavement fragilities. To provide more flexibility, the parametric regression model that expresses fragilities in terms of decision variables is developed. Developed fragilities are used as performance measures in a reliability-based optimization model. Three decision policies for rehabilitation actions are formulated and evaluated using a genetic algorithm. The multi-objective genetic algorithm is used for obtaining optimal trade-off between performance and cost. To illustrate the developed model, a numerical study is presented. The developed performance model describes well the behavior of flexible pavement before as well as after rehabilitation actions. The sensitivity measures suggest that the reliability of flexible pavements before and after rehabilitation actions can effectively be improved by providing an asphalt layer as thick as possible in the initial design and improving the subgrade stiffness. The importance measures suggest that the asphalt layer modulus at the time of rehabilitation actions represent the principal uncertainty for the performance after rehabilitation actions. Statistical validation of the developed response model shows that the response surface methodology can be efficiently used to describe pavement responses. The results for parametric regression model indicate that the developed regression models are able to express the fragilities in terms of decision variables. Numerical illustration for optimization shows that the cost minimization and reliability maximization formulations can be efficiently used in determining optimal rehabilitation policies. Pareto optimal solutions obtained from multi-objective genetic algorithm can be used to obtain trade-off between cost and performance and avoid possible conflict between two decision policies.Item Applications of Engineering and Financial Analysis to the Valuation of Investments in Railroad Infrastructure(2010-01-16) Roco, Craig E.This record of study presents the findings of industry research projects performed during a one-year doctoral internship with the Austin Rail Group of HNTB Corporation. Four main internship objectives were established that address infrastructure problems related to the railroad industry and required the integration of engineering and financial analysis to develop effective project evaluation tools. Completion of the objectives resulted in: 1. Transformation of the Federal Railroad Administration methodology currently used to perform highway-railroad grade crossing analyses to a system of equations that can easily be used to evaluate regional rail infrastructure investments. Transportation engineering equations based on queuing theory were extended to new but equivalent formulations that accommodate unlimited, discrete train performance data from computer simulations of rail networks. 2. Application of risk assessment methods and railroad accident statistics to recommend a cost-effective alternative to legislative proposals to relocate hazardous materials transported by rail around metropolitan areas. A risk analysis model was developed to predict the risk of exposure from the release of a hazardous material following a train derailment so that changes in exposure achieved by alternative risk mitigation strategies could be observed. 3. A new method of measuring the susceptibility of railroads to financial distress following the catastrophic loss of a timber railroad bridge. Economic and finance principles were used to predict financial distress by determining of the number of revenue periods required to offset economic loss. 4. Demonstration of the use of financial market data in calculating the discount rate of public railroad companies for engineering analyses that involve negotiations with the public agencies. Surface Transportation Board rulings on the determination of a railroad?s cost of equity were applied to a comparative assessment of costs of capital for Class I railroads. A hypothetical example was used to demonstrate the interrelationship between engineering design strategies and their effects on the pricing of compensation to a railroad for right-of-way acquisition. These results, in fulfillment of the doctoral internship objectives, have provided HNTB with economic decision analysis tools and a series of conclusions used to provide recommendations to the Illinois, Missouri, and Texas Departments of Transportation, the Texas Legislature, and the railroad industry.Item Constrained traffic equilibrium : impact of electric vehicles(2012-08) Jiang, Nan, Ph. D.; Waller, S. Travis; Boyles, Stephen; Damnjanovic, Ivan; Lasdon, Leon; Machemehl, Randy; Zhang, ZhanminIn many countries across the world, fossil fuels, especially petroleum, are the largest energy source for powering the socio-economic system and the transportation sector dominates the consumption of petroleum in these societies. As the petroleum price continuously climbs and the threat of global climate changes becomes more evident, the world is now facing critical challenges in reducing petroleum consumption and exploiting alternative energy sources. A massive adoption of plug-in electric vehicles (PEVs), especially battery electric vehicles (BEVs), offers a very promising approach to change the current energy consumption structure and diminish greenhouse gas emissions and other pollutants. Understanding how individual electric vehicle drivers behave subject to the technological restrictions and infrastructure availability and estimating the resulting aggregate supply-demand effects on urban transportation systems is not only critical to transportation infrastructure development, but also has determinant implications in environment and energy policy enactment. Driving PEVs inevitably changes individual’s travel and activity behaviors and calls for fundamental changes to the existing transportation network and travel demand modeling paradigms to accommodate changing cost structures, technological restrictions, and supply infrastructures. A prominent phenomenon is that all PEV drivers face a distance constraint on their driving range, given the unsatisfactory battery-charging efficiency and scarce battery-charging infrastructures in a long period of the foreseeable future. Incorporating this distance constraint and the resulting behavioral changes into transportation network equilibrium and travel demand models (static and/or dynamic) raises a series of important research questions. This dissertation focuses on analyzing the impact of a massive adoption of BEVs on urban transportation network flows. BEVs are entirely dependent on electricity and cannot go further once the battery is depleted. As a modeling requirement in its simplest form, a distance constraint should be imposed when analyzing and modeling individual behaviors and network congestions. With adding this simple constraint, this research work conceptualizes, formulates and solves mathematical programming models for a set of new BEV-based network routing and equilibrium problems. It is anticipated that the developed models and methods can be extensively used in a systematic way to analyze and evaluate a variety of system planning and policy scenarios in decision-making circumstances of BEV-related technology adoption and infrastructure development.Item Financial Implications of Engineering Decisions(2012-10-19) Aslan, VeyselWhen society fails to effectively integrate natural and constructed environments, one of the cataclysmic byproducts of this disconnect is an increased risk of natural disasters. On top of the devastation that is the aftermath of such disasters, poor planning and engineering decisions have detrimental effects on communities as they attempt to recover and rebuild. While there is an inherent difficulty in the quantification of the cost of human life, interruption in business operations, and damage to the properties, it is critical to develop plans and mitigation strategies to promote fast recovery. Traditionally insurance and reinsurance products have been used as a mitigation strategy for financing post-disaster recovery. However, there are number of problems associated with these models such as lack of liquidity, defaults, long litigation process, etc. In light of these problems, new Alternative Risk Transfer (ART) methods are introduced. The pricing of these risk mitigating instruments, however, has been mostly associated with the hazard frequency and intensity; and little recognition is made of the riskiness of the structure to be indemnified. This study proposes valuation models for catastrophe-linked ART products and insurance contracts in which the risks and value can be linked to the characteristics of the insured portfolio of constructed assets. The results show that the supply side ? structural parameters are as important as the demand ? hazard frequency, and are in a highly nonlinear relationship with financial parameters such as risk premiums and spreads.Item Identification of Owner?s Project Value Interests(2011-02-22) Gunby, Molly GaynellIdentifying the unique ways in which a project can add value to an owner?s organization is an essential part of project delivery. Every project has defined requirements, such as budget, schedule and engineering specifications that must be met; but there are other attributes of a project that are not always immediately evident; yet, when implemented, can add significant value. A delivered project that meets cost, schedule, engineering and operational requirements is not necessarily a project that provides the most value possible. To maximize the value of a project, it is first necessary to identify the ways in which it can add value. Only after that can an effective strategy be developed to exploit fully the value-adding potential of a project. However, because these value adding attributes, or value interests, are not always driven by operational or engineering requirements, they can be difficult to identify. Identification begins with understanding what aspect of a project drives the value interests. Since a single owner may engage in different types of projects and the value set of one may not be the value set of another, it is logical then to conclude it is characteristics of the project itself, not the owner, that drive the presence of value interest. It is this hypothesis, that project characteristics drive value interests, which is presented and validated in this thesis. The hypothesis is supported through the development of a mathematical model in which the parameter estimates show specific project characteristics are significant in explaining the importance of individual value interests to a project. The model was developed through binary logistic regression of industry survey data, and validated statistically and empirically. A sensitivity analysis showed the key cost- and schedule-related value interests are not significantly sensitive, and an examination of the parameter estimates showed realistic and common sense relationships are present. The methodology presented here shows that value interests are, indeed, driven by project characteristics. However, there is neither a single characteristic nor a standard set of characteristics that drive all value interests. Instead, each value interest has its own unique combination of driving characteristics.Item Modeling Dynamics of Post Disaster Recovery(2012-10-19) Nejat, AliNatural disasters result in loss of lives, damage to built facilities, and interruption of businesses. The losses are not instantaneous rather they continue to occur until the community is restored to a functional socio-economic entity. Hence, it is essential that policy makers recognize this dynamic aspect of the incurring losses and make realistic plans to enhance the recovery. However, this cannot take place without understanding how homeowners react to recovery signals. These signals can come in different ways: from policy makers showing their strong commitment to restore the community by providing financial support and/or restoration of lifeline infrastructure; or from the neighbors showing their willingness to reconstruct. The goal of this research is to develop a model that can account for homeowners? dynamic interactions in both organizational and spatial domains. Spatial domain of interactions focuses on how homeowners process signals from the environment such as neighbors reconstructing and local agencies restoring infrastructure, while organizational domain of interactions focuses on how agents process signals from other stakeholders that do not directly affect the environment like insurers. The hypothesis of this study is that these interactions significantly influence decisions to reconstruct and stay, or sell and leave. A multi-agent framework is used to capture emergent behavior such as spatial patterns and formation of clusters. The developed framework is illustrated and validated using experimental data sets.Item Modeling Risks in Infrastructure Asset Management(2012-10-19) Seyedolshohadaie, Seyed RezaThe goal of this dissertation research is to model risk in delivery, operation and maintenance phases of infrastructure asset management. More specifically, the two main objectives of this research are to quantify and measure financial risk in privatizing and operational risks in maintenance and rehabilitation of infrastructure facilities. To this end, a valuation procedure for valuing large-scale risky projects is proposed. This valuation approach is based on mean-risk portfolio optimization in which a risk-averse decision-maker seeks to maximize the expected return subject to downside risk. We show that, in complete markets, the value obtained from this approach is equal to the value obtained from the standard option pricing approach. Furthermore, we introduce Coherent Valuation Procedure (CVP) for valuing risky projects in partially complete markets. This approach leads to a lower degree of subjectivity as it only requires one parameter to incorporate user's risk preferences. Compared to the traditional discounted cash flow analysis, CVP displays a reasonable degree of sensitivity to the discount rate since only the risk-free rate is used to discount future cash flows. The application of this procedure on valuing a transportation public-private partnership is presented. %and demonstrate that the breakeven buying price of a risky project is equal to the value obtained from this valuation procedure. Secondly, a risk-based framework for prescribing optimal risk-based maintenance and rehabilitation (M&R) policies for transportation infrastructure is presented. These policies guarantee a certain performance level across the network under a predefined level of risk. The long-term model is formulated in the Markov Decision Process framework with risk-averse actions and transitional probabilities describing the uncertainty in the deterioration process. Conditional Value at Risk (CVaR) is used as the measure of risk. The steady-state risk-averse M&R policies are modeled assuming no budget restriction. To address the short-term resource allocation problem, two linear programming models are presented to generate network-level polices with different objectives. In the first model, decision-maker minimizes the total risk across the network, and in the second model, the highest risk to the network performance is minimized.Item Models and Solution Approaches for Development and Installation of PEV Infrastructure(2012-02-14) Kim, SeokThis dissertation formulates and develops models and solution approaches for plug-in electric vehicle (PEV) charging station installation. The models are formulated in the form of bilevel programming and stochastic programming problems, while a meta-heuristic method, genetic algorithm, and Monte Carlo bounding techniques are used to solve the problems. Demand for PEVs is increasing with the growing concerns about environment pollution, energy resources, and the economy. However, battery capacity in PEVs is still limited and represents one of the key barriers to a more widespread adoption of PEVs. It is expected that drivers who have long-distance commutes hesitate to replace their internal combustion engine vehicles with PEVs due to range anxiety. To address this concern, PEV infrastructure can be developed to provide re-fully status when they are needed. This dissertation is primarily focused on the development of mathematical models that can be used to support decisions regarding a charging station location and installation problem. The major parts of developing the models included identification of the problem, development of mathematical models in the form of bilevel and stochastic programming problems, and development of a solution approach using a meta-heuristic method. PEV parking building problem was formulated as a bilevel programming problem in order to consider interaction between transportation flow and a manager decisions, while the charging station installation problem was formulated as a stochastic programming problem in order to consider uncertainty in parameters. In order to find the best-quality solution, a genetic algorithm method was used because the formulation problems are NP-hard. In addition, the Monte Carlo bounding method was used to solve the stochastic program with continuous distributions. Managerial implications and recommendations for PEV parking building developers and managers were suggested in terms of sensitivity analysis. First, in the planning stage, the developer of the PEV parking building should consider long-term changes in future traffic flow and locate a PEV parking building closer to the node with the highest destination trip rate. Second, to attract more parking users, the operator needs to consider the walkability of walking links.Item Network Based Evaluation Method for Financial Analysis of Toll Roads(2011-02-22) Vajdic, NevenaThe design, build, finance and operation of public infrastructure is becoming increasingly dependent on participation of the private sector. An imposing amount of investment involved in a public private partnership agreement places financial institutions in the role of major lenders. The complexity of these agreements creates a gap in the information flow between the public sector, the private sector and financial institutions as project participants. Additionally, the public sector decisions about the network improvement actions add to the complexity of these agreements. The objective of this research is to develop a method which will allow an assessment of the effect that network improvement actions have on the project?s financial feasibility. Three common financial instruments were analyzed: bank loans, bonds and real options. Emphasis of the financial feasibility assessment was on the price of the revenue risk, as the most important risk in public private partnership agreements. Results have shown that network improvement actions can have significant impact on the price of the revenue risk. The magnitude of the impact depends on the type of instrument and the position of the road link in the network.Item Network based prediction models for coupled transportation-epidemiological systems(2011-05) Gardner, Lauren Marie; Waller, S. Travis; Sarkar, Sahotra; Walton, Michael; Damnjanovic, Ivan; Zhang, Zhanmin; Lasdon, LeonThe modern multimodal transportation system provides an extensive network for human mobility and commodity exchange around the globe. As a consequence these interactions are often accompanied by disease and other biological infectious agents. This dissertation highlights the versatility of network models in quantifying the combined impact transportation systems, ecological systems and social networks have on the epidemiological process. A set of predictive models intended to compliment the current mathematical and simulation based modeling tools are introduced. The main contribution is the incorporation of dynamic infection data, which is becoming increasingly available, but is not accounted for in previous epidemiological models. Three main problems are identified. The objective of the first problem is to identify the path of infection (for a specific disease scenario) through a social contact network by invoking the use of network based optimization algorithms and individual infection reports. This problem parallels a novel and related problem in phylodynamics, which uses genetic sequencing data to reconstruct the most likely spatiotemporal path of infection. The second problem is a macroscopic application of the methodology introduced in the first problem. The new objective is to identify links in a transportation network responsible for spreading infection into new regions (spanning from a single source) using regional level infection data (e.g. when the disease arrived at a new location). The new network structure is defined by nodes which represent regions (cites, states, countries) and links representing travel routes. The third research problem is applicable to vector-borne diseases; those diseases which are transmitted to humans through the bite of an infected vector (i.e. mosquito), including dengue and malaria. The role of the vector in the infection process inherently alters the spreading process (compared to human contact diseases), which must be addressed in prediction models. The proposed objective is to quantify the risk posed by air travel in the global spread of these types of diseases.Item A risk-based approach to modeling life-cycle costs associated with warranty specifications for transportation infrastructure(2006) Damnjanovic, Ivan; Zhang, ZhanminTo improve quality and reduce the overall costs, in recent years, many state highway agencies have started investigating innovative contracting methods, such as performance-based warranty contracting. This contracting method is structured to shift the performance-related risk from the agency to the contractor, by means of warranty provision. Even though the application of performance-based warranty contracting methods allows for a “win-win” situation, where agencies hedge the performance-related risk, and contractors have more flexibility in the design and construction processes, there are many concerns with its implementation. One of the most important concerns is how to quantify the risk cost. This dissertation is focused on the development of a robust and flexible methodological framework for quantifying the risk cost associated with warranty specifications for transportation infrastructure. The key components of this framework for studying performance warranties include: characterization of the warranty systems, development of probabilistic performance models based on the method of moments, formulation of the risk cost quantification models, and formulation of the models for determining the optimal design strategy and maintenance schedule. In this dissertation, three types of warranty systems are characterized and elaborated upon in detail: short-term, long-term, and maintenance performance warranties. To test the accuracy of the method of moments for developing reliability functions, the current AASHTO method for design of pavements is employed to provide a case study. The results from the comparison analysis of the methods of moments with Monte Carlo simulation indicate that the method of moments yields accurate predictions of the failure probabilities; in general, the quality of estimation improves as the order of the central moments in reliability indices increases. Finally, the methodology is illustrated with numerical examples to show that models for quantifying the risk cost associated with warranty specifications can be developed.