The Manual on Uniform Traffic Control Devices (MUTCD) establishes the basic principles for the design, selection, installation, operation, maintenance, and removal of traffic control devices (TCDs). The MUTCD indicates that some TCDs that are required and some are recommended, depending on the situation. However, most TCDs are not required and the decision to use a given TCD in a given situation is typically made by an engineer (or an individual working under engineering supervision) based on a variety of information. Not all engineers have the same degree of experience in making TCD decisions, and not all engineers that make these decisions have traffic engineering expertise. There are many other factors not addressed by the MUTCD that can lead to differences in the decision-making process. To assist engineers with evaluating these factors, this research developed a decision analysis process to assist engineers with making TCD decisions. The value of this research is the idea that the decision analysis process for TCD can be modeled and analyzed using appropriate factors. The developed factors include need, impact, influence, and cost. The process developed in this research applies two elements to each factor. One element compares the importance of each factor among all the other factors, and the other incorporates the engineer's judgment into the TCD decision. The first element described uses a decision analysis method, analytic hierarchy process, to determine the weights for each factor, or coefficients, as applied generally to a TCD. The second uses a mixture of quantitative and qualitative engineering judgment to determine the degree to which the factor applies to the TCD situation, or situational variable. The output of this process was a utility value that can be compared to a scale and determine the installation value of the device. This process will contribute to more uniform decisions amongst all levels of experience in TCD decision-making. Additional research that could expand on this developed process would include data collection on typical importance values for each factor as applied to a TCD and on decision scales for specific TCD situations. When applying this research, it is important to remember that it is not the intent of this process to remove engineering judgment. This is an important part of the process and should remain as such.

Capability Maturity Model Integrated (CMMI) developed by Software Engineering Institute of Carnegie Mellon University is aimed to improve the productivity of software development. From CMM to CMMI, they have been adopted worldwide. But the large numbers of unsuccessful and/or painful implementations have proved these implementations easier said than done. The software industry in Taiwan faces the challenge of global competition. Continuous improvement of productivity becomes inevitable. To achieve this goal, recently, government and non-government organizations together promote the CMMI. This thesis focuses on the Decision Analysis and Resolution of CMMI Level 3. Through the design of related methods and the development of software tools, the decision process can be more structured and more effective. Potential applications include evaluation and selection of software and hardware, outsourcing partner, tools, risk resolution alternatives or people. The typical Go/No-Go decision can also fit into it. The decision analysis methods included in this research are Multi-attribute Decision Making and Analytic Hierarchy Process(AHP). In addition, alternative screening and group decision making can be integrated into the above methods.

This study defines the optimum route planning for Electric Transmission Lines by Multicriteria Decision Analysis which is based on Geographic Information Systems (GIS). Determination of the optimum route is performed by using both the spatial and Euclidean distances between two points located on the Earth&rsquo / s surface. The criteria needed to be taken into account to define the route of the Electrical Transmission Lines were evaluated with help of the experts who are doing this business in the available system and for this study the decision about the usage of needed data such as landuse map, landuse capability map, geology map, road map, zone plan and digital elevation models is also made with their knowledge. A Matlab code, which computes the optimum distance between two transformers by using real distance (spatial distance) method and by considering materials mentioned above is written. The results are compared with the ones found from the Euclidian distance, which is the common distance finding method in the available commercial GIS softwares. The spatial resolution effect in finding the spatial distance is also analyzed. The routes obtained by two different distance computation methods are compared with the existing route. The economical expectations in finding the optimum route are also discussed.

This thesis was aimed at the development of a Geographical Information System (GIS) based model to support the Rwanda Land Use and Development Master Plan. Developing sustainable land management is the main task of this master plan. Stakeholder’s involvement was of key importance. Their demands should be analysed and visualised to support discussions and the decision-making process. Spatial Multicriteria Decision Analysis (MCDA) is a proven method for land-use planning purposes. However, most land-use planning applications focus on a specific theme, such as urban development. In addition, land-use planning is often limited to a relatively small area. This thesis focused at the development of a countrywide GIS model, containing all land-uses accommodated in three main land-use categories: urban, agriculture and conservation. The GIS model was largely based on the Land-Use Conflict Identification Strategy (LUCIS) model. Many of the goals, objectives, and subobjectives that described the earlier mentioned land-use categories were adopted from the original model. However, a significant number of them were dropped, and new were created to suit the Rwandan situation. Stakeholder’s involvement was realized by assigning weights to the goals and preference maps. The Analytical Hierarchy Process (AHP) was used as weighting method. ESRI’s ArcGIS ModelBuilder was used to give the model shape in the GIS. Firstly, suitability maps were created of all elements in the model. The suitability maps were then transformed into preference maps by weighting them. In the next step the preference maps were collapsed in three classes: low, medium and high preference. Finally, the preference maps of the three land-use categories were combined, in order to visualize conflict areas. Ortho photos proved to be useful when acting as reference for the suitability and preference maps. Despite a large number of missing datasets, the GIS model was executed to simplify the understanding. However, many of the obtained results were unreliable because of the incompleteness of datasets, and can therefore not be used for decision-making.  Unfortunately, due to the stage of the project it was not possible to obtain weights from the stakeholders, and should therefore be done when the time is right. Right Choice DSS, a very user-friendly decision support application, was proposed to use for calculating weights. To conclude, the developed GIS model integrated countrywide land-use suitability mapping and stakeholders’ wishes that can be used for discussions and decision making.

Risk management plans improve the likelihood of mission success by identifying potential failures early and planning mitigation methods to circumvent any issues. However, in the aerospace industry to date, risk management plans have typically only been used for larger and more expensive satellites, and have rarely been applied to satellites in the shape of 10 x 10 x 10 centimeter cubes, called CubeSats. Furthermore, existing risk management plans typically require experienced personnel and significant time to run the analysis. The purpose of this research was to develop two risk management software tools, the CubeSat Risk Analysis tool and the CubeSat Decision Advisor tool, which could be used by anyone with any level of experience. Moreover, the tools simply require the user to enter their mission-specific data; the software tools calculate the required analysis. The CubeSat Risk Analysis tool was developed for the purpose of reducing the subjectivity associated with estimating the likelihood and consequence of spacecraft mission risks. The tool estimates mission risk in terms of input characteristics, such as satellite form factor, mass, and development cycle. Using a historical database of small satellite missions, which was gathered in the course of this research, the software determines the mission risk root causes which are of the highest concern for the given mission. The CubeSat Decision Advisor tool uses components of decision theory such as decision trees, multi-attribute utility theory, and utility elicitation methods to determine the expected utility of a mitigation technique alternative. Based on the user’s value preference system, assessment of success probabilities, and resources required for a given mitigation technique, the tool suggests the course of action which will normatively yield the most value for the cost, personnel, and time resources required. The goals of this research were met in the development of two easily-accessible and free risk management software tools to assist in university satellite mission development. But more importantly, these tools will reach beyond the academic setting and allow small satellites to continue to evolve as a platform to accomplish educational, scientific, and military objectives. / text

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational framework. Such integrative research to link different knowledge domains faces several practical challenges. The complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. This thesis aims to overcome some of these challenges, and to demonstrate how new modeling approaches can provide successful integrative water resources research. It focuses on the development of new integrated modeling approaches which allow integration of not only physical processes but also socio-economic and environmental issues and uncertainties inherent in water resources systems. To achieve this goal, two new approaches are developed in this thesis. At first, a Bayesian network (BN)-based decision support tool is developed to conceptualize hydrological and socio-economic interaction for supporting management decisions of coupled groundwater-agricultural systems. The method demonstrates the value of combining different commonly used integrated modeling approaches. Coupled component models are applied to simulate the nonlinearity and feedbacks of strongly interacting groundwater-agricultural hydrosystems. Afterwards, a BN is used to integrate the coupled component model results with empirical knowledge and stakeholder inputs. In the second part of this thesis, a fuzzy-stochastic multiple criteria decision analysis tool is developed to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrates physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approaches are applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structures. The results show the effectiveness of the proposed methods. The first method can aid in the impact assessment of alternative management interventions on sustainability of aquifer systems while accounting for economic (agriculture) and societal interests (employment in agricultural sector) in the study area. Results from the second method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach suits to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. The new approaches can be applied to address the complexities and uncertainties inherent in water resource systems to support management decisions, while serving as a platform for stakeholder participation.

This report describes a method of incorporating decision analysis principles to enhance a simulation being created by The University of Texas at Austin’s Institute for Advanced Technology (IAT). The simulation is called Virtual Simulation Learning Platform (VSLP) and the scenario created to test the platform is called Virtual Platoon Leader (VPL). Recommendations include a method of implementing value-focused decision making, the implementation of decision tools to build a scenario within the simulation, a dialogue process between the developer and the subject matter expert, a design for the implementation of graphical user interfaces for the decision tools used to build a scenario and a user scoring methodology. / text

Due to the inherent uncertainties in ground and groundwater conditions, tunnel projects often have to face potential risks of cost overrun or schedule delay. Risk analysis has become a required tool (by insurers, Federal Transit Administration, etc.) to identify and quantify risk, as well as visualize causes and effects, and the course (chain) of events. Various efforts have been made to risk assessment and analysis by using conventional methodologies with precise probabilities. However, because of limited information or experience in similar tunnel projects, available evidence in risk assessment and analysis usually relies on judgments from experienced engineers and experts. As a result, imprecision is involved in probability evaluations. The intention of this study is to explore the use of the theory of imprecise probability as applied to risk analysis in tunneling. The goal of the methodologies proposed in this study is to deal with imprecise information without forcing the experts to commit to assessments that they do not feel comfortable with or the analyst to pick a single distribution when the available data does not warrant such precision. After a brief introduction to the theory of imprecise probability, different types of interaction between variables are studied, including unknown interaction, different types of independence, and correlated variables. Various algorithms aiming at achieving upper and lower bounds on previsions and conditional probabilities with assumed interaction type are proposed. Then, methodologies have been developed for risk registers, event trees, fault trees, and decision trees, i.e. the standard tools in risk assessment for underground projects. Corresponding algorithms are developed and illustrated by examples. Finally, several case histories of risk analysis in tunneling are revisited by using the methodologies developed in this study. All results obtained based on imprecise probabilities are compared with the results from precise probabilities. / text

There are a number of decision making problems in which Geographical Information System (GIS) has employed to organize and facilitate the procedure of analyzing the problem. These GIS-based decision problems which typically include a number of different criteria and alternatives are generally analyzed by Multicriteria Decision Analysis (MCDA).Different locations within a geographical area represent the alternatives by which the overall goal of the project is achieved. The quality of achieving the goal is evaluated by a set of criteria which should be considered in the work. Analytic Hierarchy Process (AHP) which is a powerful method of MCDA generally can organize spatial problems and decides which alternatives are most suitable for the defined problems. However due to some intrinsic uncertainty in the method, a number of authors suggest fuzzifying the method while others are against fuzzification of the AHP. The debate over fuzzifying AHP is going on and attempt for finding that was mostly in theory, and little, if any; practical comparison between the AHP and fuzzified AHP has done. This work presents a practical comparison of AHP and fuzzy AHP in a GIS-based problem, case study, for locating a dam in Costa Rica, considering different criteria. In order to perform the AHP and fuzzy AHP in the GIS-based problem and calculating weights of the criteria by the methods, some computer codes have written and developed in MATLAB. The comparisons between the AHP and fuzzy AHP methods are done on result weights and on the result final maps. The comparison between the weights is repeated on different levels of uncertainty in fuzzy AHP then all the results are compared with the result of AHP method. Also this study for checking the effect of fuzzification on results is suggested Chi-Square test as a suitable tool. Comparisons between the resulting weights of the AHP and fuzzy AHP methods show some differences between the methods. Furthermore, the Chi-Square test shows that the higher level of uncertainty in the fuzzy AHP, the greater the difference in results between the AHP and fuzzy AHP methods.

Health authority administrators were interviewed for their perspectives on what makes a good health care system; on tailored population-specific services as a way to address health inequities; and on how they perceive themselves to be making good funding decisions on the public’s behalf. The qualitative descriptive research dataset includes 24 hour-and-a-half long interviews with administrators from four BC health authorities, health region documents, memos, and field notes. Participants support the continuation of a public health care system and all participants acknowledge using tailored services as a route towards reducing health inequities. However, these identified services have not been evaluated for their overall effectiveness. When it comes to decision-making, participants describe using a series of governance and bioethical principles that help them frame what and how issues can be considered. Decision situations are framed in a way that informs them whether they need to use formal or informal processes. In both cases participants collect information that allows others to understand that they have made wise decisions. The Recognition-Primed Decision Model accurately reflects the intuitive processes that participants describe using during informal decision-making and portions of formal decision-making. However, in relation to formal decision situations, there is less alignment with existing Decision-Analysis literature. Seven practice and future research recommendations are provided: 1. Increase health authority participation in intersectoral partnerships that address non-medical determinants of health. 2. Develop new strategies for addressing health inequities. 3. Evaluate the efficacy of using tailored services beyond their ability to remove barriers to access. In addition, increase focus on testing new strategies for reducing the inequities gap. 4. Enhance existing decision-making processes by including the explicit review of decision tradeoffs, value weighting, and mechanisms for requesting revisions. 5. Focus future research on developing and evaluating the usefulness of formal decision-making tools in health authority structures and their relation to decision latitude. 6. Launch a longitudinal research study that examines how health authority expert decision-makers use judgmental heuristics and how they avoid the negative effects of bias. 7. Commission public dialogue on shifting the current illness-based system to one that is wellness based.