A seleção de projetos de investimento é uma das atividades essenciais no dia-a-dia das organizações, e, neste exercício de avaliação, é preciso lidar em geral com uma carga considerável de incerteza. Analisar apenas as características individuais dos projetos é insuficiente diante do impacto que seus aspectos relacionais pode causar nos resultados. Além disso, um fator adicional nesse processo de escolha é a carga informacional já disponível internamente, na forma de conhecimento e percepção de analistas e gestores. Mais ainda, o próprio conceito de valor neste caso depende da perspectiva de quem avalia. Motivado por estas questões, buscou-se neste trabalho elaborar uma proposta de avaliação da carteira de projetos de investimento logicamente estruturada e modular, adaptável a diversas realidades organizacionais possíveis. A montagem do procedimento otimizatório reuniu conceitos de métricas de risco e retorno de projetos, Teoria Moderna de Portfólio, Teoria da Utilidade, simulação de Monte Carlo e decomposição de Cholesky. Por fim, a utilidade da proposta foi testada via sua aplicação em amostra de projetos no segmento de óleo e gás. / The investment projects selection is one of the essential activities in day-to-day operation of companies, and in this evaluation exercise it is generally required to handle a considerable amount of uncertainty. Analysing only the individual characteristics of projects is insufficient considering the possible impact of their relational aspects in results. Furthermore an additional item in this selection process is the informational load already available internally in the form of knowledge and perception of analysts and managers. Moreover even the concept of value in this case depends on the perspective of who evaluates. Motivated by this issues, this study aimed to formulate a proposal for investment projects portfolio evaluation logically structured and modular, adaptable to various possible organizational realities. The conception of optimization procedure brought together concepts of risk and return project metrics, Modern Portfolio Theory, Utility Theory, Monte Carlo simulation and Cholesky decomposition. Finally the proposal utility was tested by its application in a sample of oil and gas projects.

In 1993, a travel study was conducted along the Wasatch front in Utah (Research Systems Group INC, 2013). The main purpose of this study was to assess travel behavior to understand the needs for future growth in Utah. Since then, the Research Service Group (RSG), conducted a new study in 2012 to understand current travel preferences in Utah. This survey, called the Residential Choice Stated Preference survey, asked respondents to make ten choice comparisons between two hypothetical homes. Each home in the choice comparison was described by different attributes, those attributes that were used are, type of neighborhood, distance from important destinations, distance from access to public transport, street design, parking availability, commute distance to work, and price. The survey was designed to determine the extent to which Utah residents prefer alternative household attributes in a choice selection. Each attribute contained multiple characteristic levels that were randomly combined to define each alternative home in each choice comparison. Those choices can be explained by Random Utility Theory. Multinomial logistic regression will be used to estimate changes in utility when alternative attribute levels are present in a choice comparison. Using the coefficient estimate for price, a marginal willingness to pay (MWTP) for each attribute level will be calculated. This paper will use two different approaches to obtain MWTP estimates. Method One will use housing and rent price to recode the price variable in dollar terms as defined in the discrete choice experiment. Method Two will recode the price variable as an average ten percent change in home value to extrapolate a one-time payment for homes. As a result, we found that it is possible to obtain willingness to pay estimates using both methods. The resulting interpretations in dollar terms became more relatable. Metropolitan planning organization can use these results to understand how residents perceive home value in dollar terms in the context of location-based attributes for homes.

To ensure compliance with specifications during construction, a formal review process, called the submittals process is typically implemented, whereby the contractor is required to submit proposals for materials, equipment, and processes for the owner’s approval within a short period of time. This procedure can be a difficult task because of lack of time, lack of information in the submittal package, difficulty in retrieving related data, and lack of defined criteria for evaluation. This research introduces development of a framework for submittal evaluation that considers the operational impact of any minor variation in the required specifications. The evaluation mechanism uses the Multi-Attribute Utility Theory (MAUT) approach, which is adaptable to the varying requirements of organizations. Through the process of analyzing the current submittal mechanism, a list of key submittals is defined and the top one (chiller) is selected to be the focus of the research. The governing criteria (evaluation parameters) are defined for the selected submittal item and categorized into two categories: inflexible and flexible. The inflexible parameters have been dealt with using checklists with predefined threshold that must be met without tolerance. Flexible parameters have been analyzed using utility functions that represent decision maker preferences and tolerance levels. Accordingly, the evaluation process considers multi-parameters to determine an overall utility for the submittal and the value-based condition for accepting it, incorporating LEED requirements. The investigation is based on data provided by three main organizations, as well as intensive meetings and interviews with experts from each participating organization. The outcome of this investigation is the development of evaluation criteria and checklist parameters that are used as the basis of a value-based evaluation, which is the core of the developed decision support system. In summary, it has been demonstrated that a decision support system for the evaluation of construction submittals can be constructed and that it will provide numerous benefits: an expedited decision process, an audit trail for decisions, more consistent and objective decisions, risk identification, internal alignment of organizational values, and improved lifecycle asset performance. The benefits were validated by demonstration, and by experts' evaluations.

Seismic rehabilitation of structural systems is an effective approach for reducing potential seismic losses such as social and economic losses. However, little or no effort has been made to develop a framework for making decisions on seismic rehabilitation of structural systems that systematically incorporates conflicting multiple criteria and uncertainties inherent in the seismic hazard and in the systems themselves. This study develops a decision support framework for seismic rehabilitation of structural systems incorporating uncertainties inherent in both the system and the seismic hazard, and demonstrates its application with detailed examples. The decision support framework developed utilizes the HAZUS method for a quick and extensive estimation of seismic losses associated with structural systems. The decision support framework allows consideration of multiple decision attributes associated with seismic losses, and multiple alternative seismic rehabilitation schemes represented by the objective performance level. Three multi-criteria decision models (MCDM) that are known to be effective for decision problems under uncertainty are employed and their applicability for decision analyses in seismic rehabilitation is investigated. These models are Equivalent Cost Analysis (ECA), Multi-Attribute Utility Theory (MAUT), and Joint Probability Decision Making (JPDM). Guidelines for selection of a MCDM that is appropriate for a given decision problem are provided to establish a flexible decision support system. The resulting decision support framework is applied to a test bed system that consists of six hospitals located in the Memphis, Tennessee, area to demonstrate its capabilities.

In this thesis, a decision model for examining prescribed risk management practices in engineering design is presented. The decision model explicitly considers the effects that design decisions under uncertainty have on the overall utility of the design process. These effects are important to consider because, according to Utility Theory, the designer should make decisions such that the expected utility is maximized. However, a significant portion of the literature neglects the costs of the design process, and focuses only on the quality of the design artifact, or at best includes its manufacture when determining the utility of an alternative. When designers neglect the costs of the design process, they cannot make tradeoffs between the costs of the design process and the quality of the artifact. As compared to previous work in this area, the decision model presented includes the effects of temporally degrading product utility on design decisions. The decision model is used to investigate the impacts of degrading product utilities in products that launch later as a result of the duration of design actions performed. In this thesis, the decision model is leveraged to investigate two key trends in engineering design resulting from increasing temporally-based costs. To support the conclusions in this thesis, quantitative evaluations of the decision model are investigated for two case studies. The conclusions are additionally supported through evaluations of the decision model in boundary plots that visualize prescribed behavior for designers over varying model parameters.

While design theories provide a foundation for representing and reasoning about design methods, existing design theories do not explicitly include uncertainty considerations or recognize tradeoffs between the design artifact and the design process. These limitations prevent the existing theories from adequately describing and explaining observed or proposed design methods. In this thesis, Rational Design Theory is introduced as a normative theoretical framework for evaluating prescriptive design methods. This new theory is based on a two-level perspective of design decisions in which the interactions between the artifact and the design process decisions are considered. Rational Design Theory consists of normative decision theory applied to design process decisions, and is complemented by a decision-theory-inspired conceptual model of design. The application of decision analysis to design process decisions provides a structured framework for the qualitative and quantitative evaluation of design methods. The qualitative evaluation capabilities are demonstrated in a review of the systematic design method of Pahl and Beitz. The quantitative evaluation capabilities are demonstrated in two example problems. In these two quantitative examples, Value of Information analysis is investigated as a strategy for deciding when to perform an analysis to gather additional information in support of a choice between two design concepts. Both quantitative examples demonstrate that Value of Information achieves very good results when compared to a more comprehensive decision analysis that allows for a sequence of analyses to be performed.

To ensure compliance with specifications during construction, a formal review process, called the submittals process is typically implemented, whereby the contractor is required to submit proposals for materials, equipment, and processes for the owner’s approval within a short period of time. This procedure can be a difficult task because of lack of time, lack of information in the submittal package, difficulty in retrieving related data, and lack of defined criteria for evaluation. This research introduces development of a framework for submittal evaluation that considers the operational impact of any minor variation in the required specifications. The evaluation mechanism uses the Multi-Attribute Utility Theory (MAUT) approach, which is adaptable to the varying requirements of organizations. Through the process of analyzing the current submittal mechanism, a list of key submittals is defined and the top one (chiller) is selected to be the focus of the research. The governing criteria (evaluation parameters) are defined for the selected submittal item and categorized into two categories: inflexible and flexible. The inflexible parameters have been dealt with using checklists with predefined threshold that must be met without tolerance. Flexible parameters have been analyzed using utility functions that represent decision maker preferences and tolerance levels. Accordingly, the evaluation process considers multi-parameters to determine an overall utility for the submittal and the value-based condition for accepting it, incorporating LEED requirements. The investigation is based on data provided by three main organizations, as well as intensive meetings and interviews with experts from each participating organization. The outcome of this investigation is the development of evaluation criteria and checklist parameters that are used as the basis of a value-based evaluation, which is the core of the developed decision support system. In summary, it has been demonstrated that a decision support system for the evaluation of construction submittals can be constructed and that it will provide numerous benefits: an expedited decision process, an audit trail for decisions, more consistent and objective decisions, risk identification, internal alignment of organizational values, and improved lifecycle asset performance. The benefits were validated by demonstration, and by experts' evaluations.

The research objective of this thesis is to formulate and demonstrate a computational framework for modeling the design decisions of engineers. This framework is intended to be descriptive in nature as opposed to prescriptive or normative; the output of the model represents a plausible result of a designer's decision making process. The framework decomposes the decision into three elements: the problem statement, the designer's beliefs about the alternatives, and the designer's preferences. Multi-attribute utility theory is used to capture designer preferences for multiple objectives under uncertainty. Machine-learning techniques are used to store the designer's knowledge and to make Bayesian inferences regarding the attributes of alternatives. These models are integrated into the framework of a Markov decision process to simulate multiple sequential decisions. The overall framework enables the designer's decision problem to be transformed into an optimization problem statement; the simulated designer selects the alternative with the maximum expected utility. Although utility theory is typically viewed as a normative decision framework, the perspective in this research is that the approach can be used in a descriptive context for modeling rational and non-time critical decisions by engineering designers. This approach is intended to enable the formalisms of utility theory to be used to design human subjects experiments involving engineers in design organizations based on pairwise lotteries and other methods for preference elicitation. The results of these experiments would substantiate the selection of parameters in the model to enable it to be used to diagnose potential problems in engineering design projects. The purpose of the decision-making framework is to enable the development of a design process simulation of an organization involved in the development of a large-scale complex engineered system such as an aircraft or spacecraft. The decision model will allow researchers to determine the broader effects of individual engineering decisions on the aggregate dynamics of the design process and the resulting performance of the designed artifact itself. To illustrate the model's applicability in this context, the framework is demonstrated on three example problems: a one-dimensional decision problem, a multidimensional turbojet design problem, and a variable fidelity analysis problem. Individual utility functions are developed for designers in a requirements-driven design problem and then combined into a multi-attribute utility function. Gaussian process models are used to represent the designer's beliefs about the alternatives, and a custom covariance function is formulated to more accurately represent a designer's uncertainty in beliefs about the design attributes.

Operations Management / (M.Sc.(Operation Research))

A seleção de projetos de investimento é uma das atividades essenciais no dia-a-dia das organizações, e, neste exercício de avaliação, é preciso lidar em geral com uma carga considerável de incerteza. Analisar apenas as características individuais dos projetos é insuficiente diante do impacto que seus aspectos relacionais pode causar nos resultados. Além disso, um fator adicional nesse processo de escolha é a carga informacional já disponível internamente, na forma de conhecimento e percepção de analistas e gestores. Mais ainda, o próprio conceito de valor neste caso depende da perspectiva de quem avalia. Motivado por estas questões, buscou-se neste trabalho elaborar uma proposta de avaliação da carteira de projetos de investimento logicamente estruturada e modular, adaptável a diversas realidades organizacionais possíveis. A montagem do procedimento otimizatório reuniu conceitos de métricas de risco e retorno de projetos, Teoria Moderna de Portfólio, Teoria da Utilidade, simulação de Monte Carlo e decomposição de Cholesky. Por fim, a utilidade da proposta foi testada via sua aplicação em amostra de projetos no segmento de óleo e gás. / The investment projects selection is one of the essential activities in day-to-day operation of companies, and in this evaluation exercise it is generally required to handle a considerable amount of uncertainty. Analysing only the individual characteristics of projects is insufficient considering the possible impact of their relational aspects in results. Furthermore an additional item in this selection process is the informational load already available internally in the form of knowledge and perception of analysts and managers. Moreover even the concept of value in this case depends on the perspective of who evaluates. Motivated by this issues, this study aimed to formulate a proposal for investment projects portfolio evaluation logically structured and modular, adaptable to various possible organizational realities. The conception of optimization procedure brought together concepts of risk and return project metrics, Modern Portfolio Theory, Utility Theory, Monte Carlo simulation and Cholesky decomposition. Finally the proposal utility was tested by its application in a sample of oil and gas projects.