As the number of vehicles increases rapidly, traffic congestion has become a serious problem in a city. Over the past years, a considerable number of studies have been made on traffic light setting. The traffic light setting problem is to investigate how to set the given traffic lights such that the total waiting time of vehicles on the roads is minimized. In this thesis, we use a graph model to represent the traffic network. On this model, some characteristics of the setting problem can be presented and analyzed. We first devise a branch and bound algorithm for obtaining the optimal solution of the traffic light setting problem. In addition, the genetic algorithm (GA), the particle swarm optimization (PSO) and the ant colony optimization (ACO) algorithm are also adopted to get the near optimal solution. Then, to extend this model, we add the assumption that each vehicle can change its direction. By comparing the results of various algorithms, we can study the impact of these algorithms on the traffic light setting problem. In our experiments, we also transform the map of Kaohsiung city into our graph model and test each algorithm on this graph.

TransCanada Corporation has proposed the Keystone XL pipeline project to transfer crude bitumen from the oil sand fields in northern Alberta, Canada, to oil refineries located in the southern part of the United States. This project has created controversy at the national level in the US and Canada and at the international level. The existence of various stakeholders with differing wants and needs has embroiled the Keystone XL in a complicated strategic dispute. This dispute was initially ignited by the potential project’s negative environmental impacts. However, economic and political issues have also played a critical role in further complicating the decision process. The objective of this study is to design a strategic decision-making system for use in assessing the Keystone XL conflict with standard and perceptual graph model methods. Standard graph model analysis consists of various steps. After identifying the decision makers (DMs) subjectively, their options and preferences are determined. Then, possible scenarios or combinations of options for these DMs are evaluated. In the next step, based on rules called solution concepts, a standard stability analysis is conducted. The perceptual graph model technique, on the other hand, considers the emotions and perceptions of DMs in a conflict to assess the existing dynamics among them. Although this technique takes its basic structure from the standard graph model technique, it presents unique insights into each DM’s perspectives toward the conflict and other DMs. This technique has been used in this study to understand how the awareness of one DM regarding other DMs’ perceptions can change reactions and strategies under different conditions regarding the Keystone XL conflict.

The present work introduces a set of solutions to extract graphs from enterprise data and facilitate the process of information search on these graphs. First of all we have defined a new graph model called the SPIDER-Graph, which models complex objects and permits to define heterogeneous graphs. Furthermore, we have developed a set of algorithms to extract the content of a database from an enterprise and to represent it in this new model. This latter representation allows us to discover relations that exist in the data but are hidden due to their poor compatibility with the classical relational model. Moreover, in order to unify the representation of all the data of the enterprise, we have developed a second approach which extracts from unstructured data an enterprise's ontology containing the most important concepts and relations that can be found in a given enterprise. Having extracted the graphs from the relational databases and documents using the enterprise ontology, we propose an approach which allows the users to extract an interaction graph between a set of chosen enterprise objects. This approach is based on a set of relations patterns extracted from the graph and the enterprise ontology concepts and relations. Finally, information retrieval is facilitated using a new visual graph query language called GraphVQL, which allows users to query graphs by drawing a pattern visually for the query. This language covers different query types from the simple selection and aggregation queries to social network analysis queries.

Conflict analysis tools are applied to brownfield negotiations in order to investigate the impacts of coalition formation and a decision maker’s (DM’s) attitudes upon the successful resolution of brownfield disputes. The concepts of attitudes within the Graph Model for Conflict Resolution (GMCR) is defined and subsequently are used, along with coalition analysis methods, to examine the redevelopment of the Kaufman Lofts property and the resolution of a post-development dispute involving Eaton’s Lofts, both located in downtown Kitchener, Ontario, Canada. Within the model of the Kaufman Lofts redevelopment, the project is broken down into three connected project conflicts: property acquisition, remediation selection and redevelopment; with the graph model applied to all three conflict nodes. The application of attitudes shows the impact of cooperation between local governments and private developers in the formation of a coalition that mutually benefits all parties. Coalition analysis, applied to the redevelopment selection conflict between Heritage Kitchener and the private developer in the Kaufman Lofts project, illustrates the importance of close collaboration between the local government and the developer. Systems methodologies implemented here for the examination of brownfield redevelopments are examined and contrasted with the economic and environmental tools commonly used in the redevelopment industry. Furthermore, coalition formation within GMCR is used to examine the negotiation of the Kyoto Protocol, to demonstrate that formal conflict resolution methods can be utilized in other areas of environmental management.

Conflict analysis tools are applied to brownfield negotiations in order to investigate the impacts of coalition formation and a decision maker’s (DM’s) attitudes upon the successful resolution of brownfield disputes. The concepts of attitudes within the Graph Model for Conflict Resolution (GMCR) is defined and subsequently are used, along with coalition analysis methods, to examine the redevelopment of the Kaufman Lofts property and the resolution of a post-development dispute involving Eaton’s Lofts, both located in downtown Kitchener, Ontario, Canada. Within the model of the Kaufman Lofts redevelopment, the project is broken down into three connected project conflicts: property acquisition, remediation selection and redevelopment; with the graph model applied to all three conflict nodes. The application of attitudes shows the impact of cooperation between local governments and private developers in the formation of a coalition that mutually benefits all parties. Coalition analysis, applied to the redevelopment selection conflict between Heritage Kitchener and the private developer in the Kaufman Lofts project, illustrates the importance of close collaboration between the local government and the developer. Systems methodologies implemented here for the examination of brownfield redevelopments are examined and contrasted with the economic and environmental tools commonly used in the redevelopment industry. Furthermore, coalition formation within GMCR is used to examine the negotiation of the Kyoto Protocol, to demonstrate that formal conflict resolution methods can be utilized in other areas of environmental management.

An enhanced attitudes methodology within the framework of the Graph Model for Conflict Resolution (GMCR) is developed and applied to a range of environmental disputes, including a sustainable development conflict, an international climate change negotiation and a selection of brownfield conflicts over a proposed transfer of ownership. GMCR and the attitudes framework are first defined and then applied to a possible Sino-American climate negotiation over reductions in greenhouse gas emissions. A formal relationship between the attitudes framework and relative preferences is defined and associated mathematical theorems, which relate the moves and solution concepts used in both types of analysis, are proven. Significant extensions of the attitudes methodology are devised in the thesis. The first, dominating attitudes is a methodology by which the importance of a decision maker’s (DM’s) attitudes can be used to evaluate the strength of a given state stability. The second, COalitions and ATtitudes (COAT), is an expansion of both the attitudes and coalitions frameworks which allows one to analyze the impact of attitudes within a collaborative decision making setting. Finally, the matrix form of attitudes, is a mathematical methodology which allows complicated solution concepts to be executed using matrix operations and thus make attitudes more adaptable to a coding environment. When applied to environmental management conflicts, these innovative expansions of the attitudes framework illustrate the importance of cooperation and diplomacy in environmental conflict resolution.

An enhanced attitudes methodology within the framework of the Graph Model for Conflict Resolution (GMCR) is developed and applied to a range of environmental disputes, including a sustainable development conflict, an international climate change negotiation and a selection of brownfield conflicts over a proposed transfer of ownership. GMCR and the attitudes framework are first defined and then applied to a possible Sino-American climate negotiation over reductions in greenhouse gas emissions. A formal relationship between the attitudes framework and relative preferences is defined and associated mathematical theorems, which relate the moves and solution concepts used in both types of analysis, are proven. Significant extensions of the attitudes methodology are devised in the thesis. The first, dominating attitudes is a methodology by which the importance of a decision maker’s (DM’s) attitudes can be used to evaluate the strength of a given state stability. The second, COalitions and ATtitudes (COAT), is an expansion of both the attitudes and coalitions frameworks which allows one to analyze the impact of attitudes within a collaborative decision making setting. Finally, the matrix form of attitudes, is a mathematical methodology which allows complicated solution concepts to be executed using matrix operations and thus make attitudes more adaptable to a coding environment. When applied to environmental management conflicts, these innovative expansions of the attitudes framework illustrate the importance of cooperation and diplomacy in environmental conflict resolution.

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Theoretical procedures are developed to account for the effect of emotion and perception in strategic conflict. The <em>possibility principle</em> facilitates modeling the effects of emotions on future scenarios contemplated by decision makers; <em>perceptual graph models</em> and a <em>graph model system</em> permit the decision makers (DMs) to experience and view the conflict independently; and <em>perceptual stability analysis</em>, which is based on individual- and meta-stability analysis techniques, is employed in analyzing graph model systems when the DMs have inconsistent perceptions. These developments improve the methodology of the Graph Model for Conflict Resolution by reconciling emotion, perception, and strategy to make predictions consistent with the actual unfolding of events. <br /><br /> Current research in neuroscience suggests that emotions are a necessary component of cognitive processes such as memory, attention, and reasoning. The somatic marker hypothesis, for example, holds that feelings are necessary to reasoning, especially during social interactions (Damasio, 1994, 2003). Somatic markers are memories of past emotions: we use them to predict future outcomes. To incorporate the effect of emotion in conflict, the underlying principle of Damasio?s hypothesis is used in developing the possibility principle, which significantly expands the paradigm of the Graph Model for Conflict Resolution of Fang, Hipel, and Kilgour (1993). <br /><br /> State identification is a crucial step in determining future scenarios for DMs. The possibility principle is integrated into the modeling stage of the Graph Model by refining the method of determining feasible states. The possibility principle enables analysts and DMs to include emotion in a conflict model, without sacrificing the parsimonious design of the Graph Model methodology, by focusing attention on two subsets of the set of feasible states: <em>hidden</em> and <em>potential</em> states. Hidden states are logically valid, feasible states that are invisible because of the presence of negative emotions such as anger and fear; potential states are logically valid, feasible states that are invisible because of missing positive emotions. Dissipating negative emotions will make the hidden states visible, while expressing the appropriate positive emotions will make the potential states visible. The possibility principle has been applied to a number of real world conflicts. In all cases, eliminating logically valid states not envisioned by any DM simplifies a conflict model substantially, expedites the analysis, and makes it an intuitive and a realistic description of the DMs' conceptualizations of the conflict. <br /><br /> A fundamental principle of the Graph Model methodology is that all DMs' directed graphs must have the same set of feasible states, which are integrated into a <em>standard</em> graph model. The possibility principle may modify the set of feasible states perceived by each DM according to his or her emotion, making it impossible to construct a single standard graph model. When logically valid states are no longer achievable for one or more DMs due to emotions, the apprehension of conflict becomes inconsistent, and resolution may become difficult to predict. Therefore, reconciling emotion and strategy requires that different apprehensions of the underlying decision problem be permitted, which can be accomplished using a perceptual graph model for each DM. A perceptual graph model inherits its primitive ingredients from a standard graph model, but reflects a DM's emotion and perception with no assumption of complete knowledge of other DMs' perceptions. <br /><br /> Each DM's perceptual graph model constitutes a complete standard graph model. Hence, conclusions drawn from a perceptual graph model provide a limited view of equilibria and predicted resolutions. A graph model system, which consists of a list of DMs' perceptual graph models, is defined to reconcile perceptions while facilitating conclusions that reflect each DM's viewpoint. However, since a DM may or may not be aware that other graph models differ from his or her own, different variants of graph model systems are required to describe conflicts. Each variant of graph model system corresponds to a configuration of awareness, which is a set of ordered combinations of DMs' viewpoints. <br /><br /> Perceptual stability analysis is a new procedure that applies to graph model systems. Its objective is to help an <em>outside</em> analyst predict possible resolutions, and gauge the robustness and sustainability of these predictions. Perceptual stability analysis takes a two-phase approach. In Phase 1, the stability of each state in each perceptual graph model is assessed from the point of view of the owner of the model, for each DM in the model, using standard or perceptual solution concepts, depending on the owner's awareness of others' perceptions. (In this research, only perceptual solution concepts for the 2-decision maker case are developed. ) In Phase 2, meta-stability analysis is employed to consolidate the stability assessments of a state in all perceptual graph models and across all variants of awareness. Distinctive modes of equilibria are defined, which reflect incompatibilities in DMs' perceptions and viewpoints but nonetheless provide important insights into possible resolutions of conflict. <br /><br /> The possibility principle and perceptual stability analysis are integrative techniques that can be used as a basis for empathetically studying the interaction of emotion and reasoning in the context of strategic conflict. In general, these new techniques expand current modeling and analysis capabilities, thereby facilitating realistic, descriptive models without exacting too great a cost in modeling complexity. In particular, these two theoretical advances enhance the applicability of the Graph Model for Conflict Resolution to real-world disputes by integrating emotion and perception, common ingredients in almost all conflicts. <br /><br /> To demonstrate that the new developments are practical, two illustrative applications to real-world conflicts are presented: the US-North Korea conflict and the confrontation between Russia and Chechen Rebels. In both cases, the analysis yields new strategic insights and improved advice.

In 2011, Oregon was one of many states in the U.S. consolidating their education governance around an early learning, K-12, and postsecondary hub. This study uses legislator-voting data to investigate the relationship between this consolidated model and endogenous policy formulation processes. This study employs a separable temporal exponential random graph model (STERGM) to investigate how an education governance shift toward consolidated authority relates to bipartisan outcomes for education-related bills over time. Oregon legislator voting networks were analyzed for cohesion, centrality, and community detection measures, as well as by legislator attributes (e.g. gender, party, and title) to test the association they had on the likelihood of forming ties with other legislators. Finally, to study the relationship of bipartisanship with legislators’ likelihood to vote commonly, I added the legislators’ political party attributes within dyads to analyze the association that having different political parties had on legislators’ common votes. The results highlight evidence of legislator networks that were very dense at each time point included in the study, with a high likelihood of forming ties. However, when Oregon shifted to centralized education governance model their legislator networks became more distributed and cohesive when compared to other years included in the longitudinal study. It is possible that such a shift prompted collaboration among legislators resulting in mutuality that increased the likelihood for underrepresented groups of legislators (e.g. females and republicans) to vote commonly with their colleagues. Aligned with previous research, this study found that centralized governing bodies reinforced by political legislation provided collaborative initiatives for the legislative community. Attending to bipartisan voting patterns dynamically through a governance shift is a valuable investigation that will provide nuanced inferences about education governance and policymaking for states making similar consolidated governance shifts in the future.