Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item Equilibrium Programming for Improved Management of Water-Resource Systems(2024) Boyd, Nathan Tyler; Gabriel, Steven A; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Effective water-resources management requires the joint consideration of multiple decision-makers as well as the physical flow of water in both built and natural environments. Traditionally, game-theory models were developed to explain the interactions of water decision-makers such as states, cities, industries, and regulators. These models account for socio-economic factors such as water supply and demand. However, they often lack insight into how water or pollution should be physically managed with respect to overland flow, streams, reservoirs, and infrastructure. Conversely, optimization-based models have accounted for these physical features but usually assume a single decision-maker who acts as a central planner. Equilibrium programming, which was developed in the field of operations research, provides a solution to this modeling dilemma. First, it can incorporate the optimization problems of multiple decision-makers into a single model. Second, the socio-economic interactions of these decision-makers can be modeled as well such as a market for balancing water supply and demand. Equilibrium programming has been widely applied to energy problems, but a few recent works have begun to explore applications in water-resource systems. These works model water-allocation markets subject to the flow of water supply from upstream to downstream as well as the nexus of water-quality management with energy markets. This dissertation applies equilibrium programming to a broader set of physical characteristics and socio-economic interactions than these recent works. Chapter 2 also focuses on the flow of water from upstream to downstream but incorporates markets for water recycling and reuse. Chapter 3 also focuses on water-quality management but uses a credit market to implement water-pollution regulations in a globally optimal manner. Chapter 4 explores alternative conceptions for socio-economic interactions beyond market-based approaches. Specifically, social learning is modeled as a means to lower the cost of water-treatment technologies. This dissertation's research contributions are significant to both the operations research community and the water-resources community. For the operations research community, this dissertation could serve as model archetypes for future research into equilibrium programming and water-resource systems. For instance, Chapter 1 organizes the research in this dissertation in terms of three themes: stream, land, and sea. For the water-resources community, this dissertation could make equilibrium programming more relevant in practice. Chapter 2 applies equilibrium programming to the Duck River Watershed (Tennessee, USA), and Chapter 3 applies it to the Anacostia River Watershed (Washington DC and Maryland, USA). The results also reinforce the importance of the relationships between socio-economic interactions and physical features in water resource systems. However, the risk aversion of the players acts as an important mediating role in the significance of these relationships. Future research could investigate mechanisms for the emergence of altruistic decision-making to improve equity among the players in water-resource systems.Item Working in Reverse: Advancing Inverse Optimization in the Fields of Equilibrium and Infrastructure Modeling(2022) Allen, Stephanie Ann; Gabriel, Steven A; Dickerson, John P; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Transportation and infrastructure modeling allows us to pursue societal aims such as improved disaster management, traffic flow, and water allocation. Equilibrium programming enables us to represent the entities involved in these applications such that we can learn more about their dynamics. These entities include transportation users and market players. However, determining the parameters in these models can be a difficult task because the entities involved in these equilibrium processes may not be able to articulate or to disclose the parameterizations that motivate them. The field of inverse optimization (IO) offers a potential solution to this problem by taking observed equilibria to these systems and using them to parameterize equilibrium models. In this dissertation, we explore the use of inverse optimization to parameterize multiple new or understudied subclasses of equilibrium problems as well as expand inverse optimization's application to new infrastructure domains. In the first project of our dissertation, our contribution to the literature is to propose that IO can be used to parameterize cost functions in multi-stage stochastic programs for disaster management and can be used in disaster support systems. We demonstrate in most of our experiments that using IO to obtain the hidden cost parameters for travel on a road network changes the protection decisions made on that road network when compared to utilizing the mean of the parameter range for the hidden parameters (also referred to as ``uniform cost''). The protection decisions made under the IO cost parameterizations versus the true cost parameterizations are similar for most of the experiments, thus lending credibility to the IO parameterizations. In the second project of our dissertation, we extend a well-known framework in the IO community to the case of jointly convex generalized Nash equilibrium problems (GNEPs). We demonstrate the utility of this framework in a multi-player transportation game in which we vary the number of players, the capacity level, and the network topology in the experiments as well as run experiments assuming the same costs among players and different costs among players. Our promising results provide evidence that our work could be used to regulate traffic flow toward aims such as reduction of emissions. In the final project of our dissertation, we explore the general parameterization of the constant vector in linear complementarity problems (LCPs), which are mathematical expressions that can represent optimization, game theory, and market models (Gabriel et al., 2012). Unlike the limited previous work on inverse optimization for LCPs, we characterize theoretical considerations regarding the inverse optimization problem for LCPs, prove that a previously proposed IO solution model can be dramatically simplified, and handle the case of multiple solution data points for the IO LCP problem. Additionally, we use our knowledge regarding LCPs and IO in a water market allocation case study, which is an application not previously explored in the IO literature, and we find that charging an additional tax on the upstream players enables the market to reach a system optimal. In sum, this dissertation contributes to the inverse optimization literature by expanding its reach in the equilibrium problem domain and by reaching new infrastructure applications.Item MULTI-AGENT UNMANNED UNDERWATER VEHICLE VALIDATION VIA ROLLING-HORIZON ROBUST GAMES(2019) Quigley, Kevin J; Gabriel, Steven A.; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Autonomy in unmanned underwater vehicle (UUV) navigation is critical for most applications due to inability of human operators to control, monitor or intervene in underwater environments. To ensure safe autonomous navigation, verification and validation (V&V) procedures are needed for various applications. This thesis proposes a game theory-based benchmark validation technique for trajectory optimization for non-cooperative UUVs. A quadratically constrained nonlinear program formulation is presented, and a "perfect-information reality" validation framework is derived by finding a Nash equilibrium to various two-player pursuit-evasion games (PEG). A Karush-Kuhn-Tucker (KKT) point to such a game represents a best-case local optimum, given perfect information available to non-cooperative agents. Rolling-horizon foresight with robust obstacles are incorporated to demonstrate incomplete information and stochastic environmental conditions. A MATLAB-GAMS interface is developed to model the rolling-horizon game, and is solved via a mixed complementarity problem (MCP), and illustrative examples show how equilibrium trajectories can serve as benchmarks for more practical real-time path planners.Item Diffusion Dynamics in Interconnected Communities(2015) Wei, Xiaoya; Abed, Eyad H.; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation, multi-community-based Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Susceptible (SIS) models of infection/innovation diffusion are introduced for heterogeneous social networks in which agents are viewed as belonging to one of a finite number of communities. Agents are assumed to have well-mixed interactions within and between communities. The communities are connected through a backbone graph which defines an overall network structure for the models. The models are used to determine conditions for outbreak of an initial infection. The role of the strengths of the connections between communities in the development of an outbreak as well as long-term behavior of the diffusion is also studied. Percolation theory is brought to bear on these questions as an independent approach separate from the main dynamic multi-community modeling approach of the dissertation. Results obtained using both approaches are compared and found to be in agreement in the limit of infinitely large populations in all communities. Based on the proposed models, three classes of marketing problems are formulated and studied: referral marketing, seeding marketing and dynamic marketing. It is found that referral marketing can be optimized relatively easily because the associated optimization problem can be formulated as a convex optimization. Also, both seeding marketing and dynamic marketing are shown to enjoy a useful property, namely ``continuous monotone submodularity." Based on this property, a greedy heuristic is proposed which yields solutions with approximation ratio no less than 1-1/e. Also, dynamic marketing for SIS models is reformulated into an equivalent convex optimization to obtain an optimal solution. Both cost minimization and trade-off of cost and profit are analyzed. Next, the proposed modeling framework is applied to study competition of multiple companies in marketing of similar products. Marketing of two classes of such products are considered, namely marketing of durable consumer goods (DCG) and fast-moving consumer goods (FMCG). It is shown that an epsilon-equilibrium exists in the DCG marketing game and a pure Nash equilibrium exists in the FMCG marketing game. The Price of Anarchy (PoA) in both marketing games is found to be bounded by 2. Also, it is shown that any two Nash equilibria for the FMCG marketing game agree almost everywhere, and a distributed algorithm converging to the Nash equilibrium is designed for the FMCG marketing game. Finally, a preliminary investigation is carried out to explore possible concepts of network centrality for diffusions. In a diffusion process, the centrality of a node should reflect the influence that the node has on the network over time. Among the preliminary observations in this work, it is found that when an infection does not break out, diffusion centrality is closely related to Katz centrality; when an infection does break out, diffusion centrality is closely related to eigenvector centrality.Item The utility of NGO interventions: Influences on terrorist activity.(2015) Hodwitz, Omi; Dugan, Laura; Criminology and Criminal Justice; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Terrorism studies have increased following the attacks in the United States on September 11, 2001. While a great deal of research has focused on the influence of state-sponsored counterterrorism strategies on terrorist activities, limited attention has been directed towards examining the influence of non-state actors on terrorist organizations (TOs). This dissertation seeks to assess the role that an influential but often overlooked player may have on terrorist activity: the non-governmental organization (NGO). Many TOs and NGOs engage in similar campaigns, primarily providing services or advocating for a shared constituency or minority that experiences suffering at the hands of a majority, usually the state. Both TOs and NGOs require the support of the constituents in order to maintain group legitimacy, fundraise, and recruit. In addition, both vie for media attention in order to publicize the issue, radicalize the larger community, and exert pressure on the state. Public support and attention is limited and difficult to acquire, placing TOs and NGOs in competition. As such, within the rational choice and game theoretic frameworks, when faced with an NGO competitor, TOs are hypothesized to adjust their activities in order to gain constituent support, media attention, and to eliminate the competition. Using data from the Global Terrorism Database (GTD), this dissertation assesses the influence that Amnesty International, Human Rights Watch, International Committee of the Red Cross, and local NGOs have on TOs in Algeria, Lebanon, and Turkey between 1987 and 2011. Results from autoregressive Poisson and negative binomial models demonstrate limited support for the hypothesized relationships. NGOs appear to have a marginal influence on TO activities in Algeria, an extremely limited impact in Lebanon, and no relationship in Turkey. Overall findings suggest two conclusions: NGO activities, in general, do not appear to escalate TO violence and NGO campaign activities specifically focused on de-escalating TO violence appear to be ineffective in these three countries. Replication is needed in additional countries to substantiate these findings.Item Dynamic Spectrum Allocation and Sharing in Cognitive Cooperative Networks(2009) Wang, Beibei; Liu, K. J. Ray; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The dramatic increase of service quality and channel capacity in wireless networks is severely limited by the scarcity of energy and bandwidth, which are the two fundamental resources for communications. New communications and networking paradigms such as cooperative communication and cognitive radio networks emerged in recent years that can intelligently and efficiently utilize these scarce resources. With the development of these new techniques, how to design efficient spectrum allocation and sharing schemes becomes very important, due to the challenges brought by the new techniques. In this dissertation we have investigated several critical issues in spectrum allocation and sharing and address these challenges. Due to limited network resources in a multiuser radio environment, a particular user may try to exploit the resources for self-enrichment, which in turn may prompt other users to behave the same way. In addition, cognitive users are able to make intelligent decisions on spectrum usage and communication parameters based on the sensed spectrum dynamics and other users' decisions. Thus, it is important to analyze the intelligent behavior and complicated interactions of cognitive users via game-theoretic approaches. Moreover, the radio environment is highly dynamic, subject to shadowing/fading, user mobility in space/frequency domains, traffic variations, and etc. Such dynamics brings a lot of overhead when users try to optimize system performance through information exchange in real-time. Hence, statistical modeling of spectrum variations becomes essential in order to achieve near-optimal solutions on average. In this dissertation, we first study a stochastic modeling approach for dynamic spectrum access. Since the radio spectrum environment is highly dynamic, we model the traffic variations in dynamic spectrum access using continuous-time Markov chains that characterizes future traffic patterns, and optimize access probabilities to reduce performance degradation due to co-channel interference. Second, we propose an evolutionary game framework for cooperative spectrum sensing with selfish users, and develop the optimal collaboration strategy that has better performance than fully cooperating strategy. Further, we study user cooperation enforcement for cooperative networks with selfish users. We model the optimal relay selection and power control problem as a Stackelberg game, and consider the joint benefits of source nodes as buyers and relay nodes as sellers. The proposed scheme achieves the same performance compared to traditional centralized optimization while reducing the signaling overhead. Finally, we investigate possible attacks on cooperative spectrum sensing under the evolutionary sensing game framework, and analyze their damage both theoretically and by simulations.Item Robust Network Trust Establishment for Collaborative Applications and Protocols(2007-05-07) Theodorakopoulos, Georgios Efthymios; Baras, John S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In networks without centralized control (e.g. ad-hoc or peer-to-peer networks) the users cannot always be assumed to follow the protocol that they are supposed to. They will cooperate in the operation of the network to the extent that they achieve their own personal objectives. The decision to cooperate depends on the trust relations that users develop for each other through repeated interactions. Users who have not interacted directly with each other can use direct trust relations, generated by others, in a transitive way as a type of recommendation. Network operation and trust generation can be affected by malicious users, who have different objectives, and against whom any proposed solution needs to be robust. We model the generation of trust relations using repeated games of incomplete information to capture the repetitive operation of the network, as well as the lack of information of each user about the others' objectives. We find equilibria that provide solutions for the legitimate users against which the malicious users cannot improve their gains. The transitive computation of trust is modeled using semiring operators. This algebraic model allows us to generalize various trust computation algorithms. More importantly, we find the maximum distortion that a malicious user can cause to the trust computation by changing the reported trust value of a trust relation.Item Three essays on institutions and economic development(2006-08-23) Shepotylo, Oleksandr; Murrell, Peter; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Institutions are humanly devised constraints that shape interactions between people. Changing those constraints affects people's incentives and, therefore, affects economic, political, and social outcomes. Studying institutional arrangements helps to shed some light on why there is a high variation of the level of economic development across countries. These theses address the questions of how institutions are formed, how institutional changes affect incentives, and how they influence economic development. The first chapter studies the effect of change in the rule that assign points in soccer on optimal strategies of soccer teams playing in a tournament. It demonstrates that the change in the rule increases incentives of teams to collude in order to trade points. It also has heterogeneous effects on top and lesser teams. Second chapter looks at impact of good regional governance infrastructure on inflows of foreign direct investment (FDI) in 24 transition countries from 1993 to 2003. The model takes into account spatial spillovers and spatially correlated error terms. It is estimated by a recently developed generalized method of moment (GMM) three-stage procedure. The results show that the regional quality of institutions is an important factor that explains variations in FDI inflows. The positive effect of good regional governance dominates the effect of better developed regional markets. The third chapter investigates determinants of the quality of governance inside a country. The main finding is the importance of relative geographical location: good governance in the neighboring countries has a positive impact on quality of governance inside a particular country. Spatial links work mostly through long-term determinants of governance that include culture, legal system, and colonial history. At the same time, the closest neighbors have the strongest impact on quality of governance, while cultural and colonial " neighbors" that are not close geographically, have smaller impact on the local institutional development. According to our results, cross-country regressions that do not take into account spatial interdependence of countries produce biased estimation of the coefficients and incorrect inference of variance-covariance matrix.Item Interjurisdictional Competition and Urban Area Fragmentation(2005-05-26) Aylward, Stephen Richard; Oppenheimer, Joe A.; Government and Politics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The collective action problem in political science examines the circumstances under which groups can be successfully formed and maintained. While earlier generations of political scientists believed that groups developed in democracies because of the nature of democratic culture and procedures, Mancur Olson (The Logic of Collective Action, 1965) demonstrated that free-riding doomed many attempts at collective action unless selective benefits were granted to members--hence automobile association members receive free travel services, for example. Subsequent theories posited other reasons for successful collective action, such as communication, leadership and anticipated returns from joining. Tests of these hypotheses have taken place primarily in laboratory experiments. This study conducts a real-world natural experiment, examining interjurisdictional competition (IJC)--a government's offer of incentives for businesses to locate within its environs as opposed to the territories of others--in the setting of urbanized areas of various degrees of fragmentation (political organization as one, several or many local governments). If the free-rider hypothesis is true, IJC would increase with higher fragmentation. As the "free-rider" title suggests, IJC has been portrayed in game theory as a prisoners' dilemma. However, more detailed analysis in this study reveals several possible games, each posing a related collective action problem. Methodologically, additive indices from a nationwide survey of economic development practices measure the intensity of IJC effort. Urban area fragmentation is represented by indices using the Hirschman-Herfindahl Index method. The major hypothesis--IJC is a function of fragmentation--is analyzed using OLS regression. The regressions refute the free-rider hypothesis. The statistical analysis then examines the subsequent explanations of collective action. Anticipated returns cannot be substantiated; however, civil society-based indicators show communication and leadership to be causes of successful collective action. Finally, a case study of Hampton Roads (the Virginia Beach-Norfolk-Newport News, Virginia metropolitan area) provides a historical narrative of the efficacy of communication and leadership in successful collective action as well as a possible example of game transition from the prisoners' dilemma to an assurance game.