O estudo de sistemas logísticos envolve a concatenação de elementos estratégicos e operacionais, comumente compondo sistemas com múltiplas facetas, objetivos antagônicos e grande número de alternativas. Nesse contexto, o presente trabalho discute a utilização de análise de decisão multicritério (MCDA), simulação de eventos discretos (SED) e otimização para simulação. A metodologia MCDA captura, mensura e pondera os objetivos e valores dos tomadores de decisão. Por sua vez, a SED representa o sistema estudado com alto nível de detalhamento, permitindo a avaliação de diversas configurações do sistema. Por fim, métodos de otimização para simulação possibilitam a busca e comparação de alternativas mais eficientes. As três metodologias são avaliadas, identificando suas vantagens, desvantagens e complementaridades quando aplicadas a sistemas logísticos. Através da aplicação de um estudo de caso sobre o dimensionamento de um sistema de transporte, constatou-se que: a) a SED incorporou detalhes importantes para a avaliação mais precisa de vários indicadores de desempenho b) a metodologia MCDA possibilitou a captura de vários objetivos e valores, propiciando a realização de tradeoffs robustos; c) um método de busca exaustiva e técnicas de redução de variância permitiram a comparação das alternativas em tempos computacionais reduzidos. Por fim, conclui-se que a metodologia híbrida apresentada expande o potencial de aplicação da SED em sistemas logísticos complexos. / A logistic system study involves strategic and operational elements, commonly composing multi-faceted systems with antagonistic goals and large number of alternatives. In this context, this thesis discusses the use of multi-criteria decision analysis (MCDA), discrete event simulation (DES) and optimization for simulation. The MCDA methodology captures, measures and weighs the goals and values of decision makers. DES is useful for representing systems with high level of detail, allowing the evaluation of several system configurations. Finally, optimization for simulation procedures are useful for searching and comparing more efficient alternatives. These three methodologies are assessed and their advantages, disadvantages, and complementarities are identified for logistics systems applications. Through a case study of a transportation system, we conclude that: a) the SED incorporated important details for more precise evaluation of various performance indicators b) the MCDA methodology was useful to capture several goals and values, so that robust tradeoffs could be carried out c) an exhaustive search routine and variance reduction techniques allowed the comparison of several alternatives in feasible computational times. Finally, we conclude that the presented hybrid methodology expands the application of DES to complex logistics systems.

Desenvolver programas de conservação, a partir do conhecimento prévio do estado dos pavimentos, possibilita obter determinados níveis de qualidade em toda a rede viária. No entanto, num cenário de carência financeira, manter esses níveis de qualidade só é possível se as decisões forem tomadas considerando as seções mais prioritárias às atividades de manutenção e reabilitação (M&R) dos pavimentos. O objetivo geral deste trabalho é propor um modelo de priorização de vias, baseado na metodologia de análise multicritério agregada a um sistema de informação geográfica (SIG), considerando critérios objetivos e subjetivos no apoio à tomada de decisão. Fez parte deste trabalho uma pesquisa sobre a situação atual referente aos procedimentos de gerência da conservação de pavimentos utilizados em cidades médias brasileiras. Foi realizado um estudo de caso, na cidade de São Carlos - SP, utilizando um levantamento preliminar da condição do pavimento e de suas características físicas e geométricas, no que se refere às seções de vias urbanas, que são de responsabilidade da prefeitura. O modelo desenvolvido neste trabalho, que utiliza AHP (Analytic Hierarchy Process) e SIG, é adequado à realidade das cidades médias brasileiras, mas mantém a viabilidade de aplicação em cidades de outras dimensões, desde que as particularidades dessas cidades sejam consideradas. É destinado a auxiliar administradores de órgãos governamentais que têm a função de avaliar e planejar as intervenções de conservação em vias urbanas pavimentadas. / The development of conservation programs, starting from the previous knowledge of pavements condition, makes possible to maintain certain quality levels in the roadway system. However, in a lack of budget scenario, to achieve those quality levels the decisions have to be taken considering a pavement maintenance and rehabilitation (M&R) prioritization program. The general objective of this work is to propose urban roadways prioritization model based on multicriteria decision analysis aggregated to geographical information system (GIS), considering objective and subjective criteria in the decision support. A case study was performed at the city of São Carlos, state of São Paulo, Brazil, using a preliminary study of pavement condition and physical and geometric characteristics. It was also performed a research about the current situation regarding the procedures for pavement maintenance and rehabilitation management in brazilian medium-sized cities. The model developed in this work, that uses AHP (Analytic Hierarchy Process) and GIS is adapted to the reality of the brazilian medium-sized cities, but it maintains the application viability in cities of other dimensions, since the particularities of those cities are considered. It is dedicated to help administrators of government agency responsible for the evaluation of urban roads and pavement conservation planning.

A relevância da infraestrutura de transporte para incrementos em produtividade, induzindo ao desenvolvimento socioeconômico de determinada região é amplamente reconhecida. O Brasil, no entanto, apresenta sérias deficiências em relação à sua infraestrutura de transporte, oriundas de seu desenvolvimento histórico e da redução de níveis de investimentos públicos no setor nas últimas décadas. Estas deficiências traduzem-se em grande concentração no modal rodoviário para o transporte de cargas, menos eficiente do que os modais ferroviário e hidroviário, resultando em reduzida competitividade das organizações nacionais. Neste contexto, objetivou-se no presente trabalho a proposição de um modelo para avaliação e seleção de investimentos em infraestrutura de transporte de cargas, considerando-se seu caráter multidimensional. Para isso, foi proposta metodologia integrando os conceitos de análise de decisão multicritério e de programação matemática, representados pela teoria de utilidade multiatributo (Multi-Attribute Utility Theory - MAUT) e por problema de otimização de fluxos em rede (Minimum Cost Network Flow Problem - MCNFP), respectivamente. No desenvolvimento do modelo foram contemplados critérios de avaliação referentes às dimensões de análise financeira, operacional e ambiental. Posteriormente, foi considerada a aplicação de versões do modelo proposto com diferentes números de períodos de análise em caso ilustrativo, representativo da rede de transporte disponível e planejada da região Norte do Brasil. A aplicação das diversas versões do modelo proposto, de forma geral, apresentou resultados compatíveis com as teorias relacionadas à avaliação deste problema de decisão, incluindo indução à multimodalidade. Algumas versões do modelo apresentaram violações em algumas de suas restrições. Estes resultados adversos não foram plenamente eliminados, devido a limitações das ferramentas adotadas para aplicação. No entanto, foi possível a correção manual destas violações, resultando em soluções viáveis que, apesar de não serem consideradas ótimas, são mais completas do que soluções obtidas por meio de metodologias unidimensionais de análise. Por fim, foram apresentadas recomendações para condução de trabalhos futuros visando eliminação dos resultados adversos do modelo proposto e complementação de sua análise. / The role of transport infrastructure in productivity increases leading to regional social-economic development is widely recognized. Brazil, however, has serious deficiencies in its transport infrastructure, rooted in the country\'s historical development and in the recent decades\' reduction of public investment in the sector. These deficiencies can be observed in Brazil\'s strong focus on roads for cargo transportation, which besides being less efficient than rail and waterways, results in reduced competitiveness of national enterprises. In this context, the aim of this work was to propose a model for evaluating and selecting investments in freight\'s transportation infrastructure, considering its multidimensional character. It was proposed a methodology integrating the concepts of multi-criteria decision analysis and mathematical programming, represented by the Multi-Attribute Utility Theory (MAUT) along with the Minimum Cost Network Flow Problem (MCNFP). The developed model included financial, operational and environmental analysis evaluation criteria. Subsequently, this study applied the proposed model into a case study of the transportation network, available and planned, of the Northern region of Brazil. Overall, the application of various versions of the proposed model yielded results consistent with related evaluation and decision making theories, including induction of multimodality. Some versions of the model presented some violations of its restrictions. These adverse results were not fully eliminated due to the limitations of the application tools utilized. It was possible, however, to manually correct these violations and obtain viable solutions that, while cannot be considered optimal, are more complete than those obtained by single dimension analysis. Finally, recommendations were made for future studies aiming at eliminating the proposed model\'s adverse outcomes, and complementing its analysis.

No setor de energia elétrica, a área que se dedica ao estudo da inserção de novos parques geradores de energia no sistema é denominada planejamento da expansão da geração. Nesta área, as decisões de localização e instalação de novas usinas devem ser amplamente analisadas, a fim de se obter os diversos cenários proporcionados pelas alternativas geradas. Por uma série de fatores, o sistema de geração elétrico brasileiro, com predominância hidroelétrica, tende a ser gradualmente alterada pela inserção de usinas termoelétricas (UTEs). O problema de localização de UTEs envolve um grande número de variáveis através do qual deve ser possível analisar a importância e contribuição de cada uma. O objetivo geral deste trabalho é o desenvolvimento de um modelo de localização de usinas termoelétricas, aqui denominado SIGTE (Sistema de Informação Geográfica para Geração Termoelétrica), o qual integra as funcionalidades das ferramentas SIGs (Sistemas de Informação Geográfica) e dos métodos de decisão multicritério. A partir de uma visão global da área estudada, as componentes espaciais do problema (localização dos municípios, tipos de transporte, linhas de transmissão de diferentes tensões, áreas de preservação ambiental, etc.) podem ter uma representação mais próxima da realidade e critérios ambientais podem ser incluídos na análise. Além disso, o SIGTE permite a inserção de novas variáveis de decisão sem prejuízo da abordagem. O modelo desenvolvido foi aplicado para a realidade do Estado de São Paulo, mas deixando claro a viabilidade de uso do modelo para outro sistema ou região, com a devida atualização dos bancos de dados correspondentes. Este modelo é designado para auxiliar empreendedores que venham a ter interesse em construir uma usina ou órgãos governamentais que possuem a função de avaliar e deferir ou não a licença de instalação e operação de usinas. / In the electric power industry, there is an area devoted to study alternatives for the expansion of the energy generation system. The decisions regarding the location and installation of new plants ought to be thoroughly analyzed in that planning activity, in order to foresee the likely scenarios resulting from the combination of distinct alternatives. For a number of reasons, the predominantly hydroelectric generation system historically set in Brazil tends to be gradually altered by the introduction of thermoelectric power plants (TPPs). The site selection problem involves, in the case of TPPs, a large number of variables, which contribute to the analysis process in various ways and with different levels of importance. The general goal of this work is the development of a location model of thermoelectric plants, here named SIGTE (an acronym for Geographic Information System for Thermoelectric Generation), which integrates the functionalities of the GIS tools (Geographic Information Systems) and multicriteria decision methods. Starting from an overall view of the studied area, this combination of techniques ensures a more realistic representation of the spatial components of the problem (e.g., the location of the municipalities, the transportation alternatives, the different voltages of transmission lines, areas of environmental preservation, etc.) It thus allows a straightforward inclusion of environmental criteria in the analysis. In addition, the SIGTE framework is also flexible enough to incorporate new decisions variables. The model was applied in a case study carried out in the state of Sao Paulo, although it can be easily adapted for use in other systems or geographical areas given that the corresponding databases are available. SIGTE was envisaged to be a supporting tool to public and private stakeholders interested in building new power plants or to governmental agencies in charge of the regulation mechanisms required for the installation nd operation of plants.

This research assesses the impacts of developing shale gas in the UK, with the focus of determining whether or not it is possible to develop it sustainably and how it could affect the electricity and gas mix. There is much uncertainty on the impacts of developing shale gas in the UK, as the country is currently in the early stages of exploration drilling and the majority of studies which have been carried out to analyse the effects of shale gas development have been US specific. To address these questions, the environmental, economic and social sustainability have been assessed and the results integrated to evaluate the overall sustainability. The impacts of shale gas electricity have been assessed so that it can be compared with other electricity generation technologies (coal, nuclear, renewables etc.), to ascertain its impacts on the UK electricity mix. Life cycle assessment is used to evaluate the environmental sustainability of shale gas electricity (and other options), while life cycle costing and social sustainability assessment have been used to evaluate the economic and social sustainability. Multi-criteria decision analysis has been used to combine the results of three to evaluate the overall sustainability. The incorporation of shale gas into the UK electricity mix is modelled in two future scenarios for the year 2030. The scenarios compare different levels of shale gas penetration: low and high. The results show that shale gas will have little effect on improving the environmental sustainability and energy security of the UK’s electricity mix, but could help ease energy prices. In comparison with other options, shale gas is not a sustainable option, as it has higher environmental impacts than the non-fossil fuels and conventional gas and liquefied natural gas: 460 g CO2-Eq. is emitted from the shale gas electricity life cycle, while conventional gas emits 420 g CO2-Eq. and wind 12 g CO2-Eq. The power plant and drilling fluid are the main impact hot spots in the life cycle, while hydraulic fracturing contributes a small amount (5%). In addition to this, there are a number of social barriers which need to be addressed, notably: traffic volume and congestion could increase by up to 31%, public support is low and wastewater produced from hydraulic fracturing could put strain on wastewater treatment facilities. However, the results indicate that shale gas is economically viable, as the cost of electricity is cheaper than solar photovoltaic, biomass and hydroelectricity (9.59 p/kWh vs 16.90, 11.90 and 14.40 p/kWh, respectively). The results of this thesis show that there is a trade-off in the impacts, but because of its poor environmental and social ratings shale gas is not the best option for UK electricity. The results also identify areas for improvement which should be targeted, as well as policy recommendations for best practice and regulation if shale gas were to be developed in the UK.

Desenvolver programas de conservação, a partir do conhecimento prévio do estado dos pavimentos, possibilita obter determinados níveis de qualidade em toda a rede viária. No entanto, num cenário de carência financeira, manter esses níveis de qualidade só é possível se as decisões forem tomadas considerando as seções mais prioritárias às atividades de manutenção e reabilitação (M&R) dos pavimentos. O objetivo geral deste trabalho é propor um modelo de priorização de vias, baseado na metodologia de análise multicritério agregada a um sistema de informação geográfica (SIG), considerando critérios objetivos e subjetivos no apoio à tomada de decisão. Fez parte deste trabalho uma pesquisa sobre a situação atual referente aos procedimentos de gerência da conservação de pavimentos utilizados em cidades médias brasileiras. Foi realizado um estudo de caso, na cidade de São Carlos - SP, utilizando um levantamento preliminar da condição do pavimento e de suas características físicas e geométricas, no que se refere às seções de vias urbanas, que são de responsabilidade da prefeitura. O modelo desenvolvido neste trabalho, que utiliza AHP (Analytic Hierarchy Process) e SIG, é adequado à realidade das cidades médias brasileiras, mas mantém a viabilidade de aplicação em cidades de outras dimensões, desde que as particularidades dessas cidades sejam consideradas. É destinado a auxiliar administradores de órgãos governamentais que têm a função de avaliar e planejar as intervenções de conservação em vias urbanas pavimentadas. / The development of conservation programs, starting from the previous knowledge of pavements condition, makes possible to maintain certain quality levels in the roadway system. However, in a lack of budget scenario, to achieve those quality levels the decisions have to be taken considering a pavement maintenance and rehabilitation (M&R) prioritization program. The general objective of this work is to propose urban roadways prioritization model based on multicriteria decision analysis aggregated to geographical information system (GIS), considering objective and subjective criteria in the decision support. A case study was performed at the city of São Carlos, state of São Paulo, Brazil, using a preliminary study of pavement condition and physical and geometric characteristics. It was also performed a research about the current situation regarding the procedures for pavement maintenance and rehabilitation management in brazilian medium-sized cities. The model developed in this work, that uses AHP (Analytic Hierarchy Process) and GIS is adapted to the reality of the brazilian medium-sized cities, but it maintains the application viability in cities of other dimensions, since the particularities of those cities are considered. It is dedicated to help administrators of government agency responsible for the evaluation of urban roads and pavement conservation planning.

En sciences économiques, l'une des questions centrales concerne l'allocation des ressources rares et plus particulièrement leur répartition. La décision apparait ainsi au cœur des thématiques économiques, que ce soit en micro-économie ou en macro-économie. Dans un premier temps, nous revenons sur le fait que l’information, élément central de la prise de décision, est imparfaite. En utilisant la théorie des ensembles flous, qui a pour objet de capturer l’imprécision, nous construisons un nombre flou nommé nombre flou C-Shape qui permet de capter la sensibilité du preneur de décision. Nous étudions ensuite la théorie de la décision au travers de deux axes de recherche à savoir (1) la recherche opérationnelle couplée à la théorie des jeux et (2) l’aide à la décision. En premier lieu, Nous faisons une analogie entre la fonction distance et la fonction d’appartenance. Grâce à l’hypothèse de B-convexité et à la fonction C-Shape nous construisons des classes de jeux pour lesquels les joueurs peuvent être optimistes, pessimistes ou neutres, et pour lesquels l’existence d’équilibre de Nash est avérée. Enfin, concernant l’aide à la décision, nous utilisons la fonction C-Shape pour caractériser un nouveau type de critère nommé pseudo critère C-Shape qui permet de considérer les alternatives comme substituables. Ceci permet de prendre en compte, par exemple le contexte institutionnel dans lequel la prise de décision est prise. / Determining the allocation and the distribution of scarce resources is fundamental in economics. Thus, decision theory is the cornerstone of economic theory. In this thesis, we first provide a state of the art insisting on the fact that information, that is a central element of decision-making, is imperfect. Secondly, using fuzzy set theory, which aims to capture imprecision, we construct a fuzzy number, so-called C-Shape that captures the sensitivity of the decision-maker. Thirdly, we study decision theory through two key concepts of operation research: (1) game theory and (2) multi-criteria decision making. We provide an analogy between the gauge functions of convex sets and the membership functions arising in fuzzy set theory. Coupling a suitable notion of -convexity with the C-Shape function, we introduce a class of games for which the players can be optimistic, pessimistic or neutral. In addition the existence of Nash equilibrium is proved for such a class of games. Finally, concerning multi-criteria decision analysis, we use the C-Shape functions to characterize a new type of criteria called C-Shape pseudo-criterion, which makes possible to consider the alternatives as substitutable. This should be of interest to take into account, for example, the institutional context in which decision-making is taken.

Infrastructure privatization decisions have an enormous financial and social impact on all stakeholders, including the public sector, the private sector, and the general public. Appropriate privatization decisions, however, are difficult to make due to the conflicting nature of the objectives of the various stakeholders. This research introduces a multi-criteria decision-making framework for evaluating and comparing a wide range of privatization schemes for infrastructure facilities. The framework is designed to resolve conflicts that arise because of the varying points of view of the stakeholders, and accordingly, determine the most appropriate decision that satisfies all stakeholders’ preferences. The developed framework is expected to help in re-engineering the traditional conflict resolution process, particularly for construction conflict resolution and infrastructure privatization decisions. The framework provides decision support at the management level through three successive decision support processes related to 1. Screening of feasible solutions using the Elimination Method of multiple criteria decision analysis (MCDA); 2. Analyzing the actions and counteractions of decision makers using conflict resolution and decision stability concepts to determine the most stable resolution; and 3. Considering the uncertainty in decision maker’s preferences using Info-gap Theory to evaluate the robustness of varying uncertainty levels of the decisions. Based on the research, a procedure and a decision support system (DSS) have been developed and tested on real-life case studies of a wastewater treatment plant and a construction conflict. The results of the two case studies show that the proposed DSS can be used to support decisions effectively with respect to both construction conflicts and infrastructure privatization. The developed system is simple to apply and can therefore save time and avoid the costs associated with unsatisfactory decisions. This research is expected to contribute significantly to the understanding and selecting of proper Public-Private-Partnership (PPP) programs for infrastructure assets.

Infrastructure privatization decisions have an enormous financial and social impact on all stakeholders, including the public sector, the private sector, and the general public. Appropriate privatization decisions, however, are difficult to make due to the conflicting nature of the objectives of the various stakeholders. This research introduces a multi-criteria decision-making framework for evaluating and comparing a wide range of privatization schemes for infrastructure facilities. The framework is designed to resolve conflicts that arise because of the varying points of view of the stakeholders, and accordingly, determine the most appropriate decision that satisfies all stakeholders’ preferences. The developed framework is expected to help in re-engineering the traditional conflict resolution process, particularly for construction conflict resolution and infrastructure privatization decisions. The framework provides decision support at the management level through three successive decision support processes related to 1. Screening of feasible solutions using the Elimination Method of multiple criteria decision analysis (MCDA); 2. Analyzing the actions and counteractions of decision makers using conflict resolution and decision stability concepts to determine the most stable resolution; and 3. Considering the uncertainty in decision maker’s preferences using Info-gap Theory to evaluate the robustness of varying uncertainty levels of the decisions. Based on the research, a procedure and a decision support system (DSS) have been developed and tested on real-life case studies of a wastewater treatment plant and a construction conflict. The results of the two case studies show that the proposed DSS can be used to support decisions effectively with respect to both construction conflicts and infrastructure privatization. The developed system is simple to apply and can therefore save time and avoid the costs associated with unsatisfactory decisions. This research is expected to contribute significantly to the understanding and selecting of proper Public-Private-Partnership (PPP) programs for infrastructure assets.

Nutrients are the number one water pollution problem for U.S. lakes, reservoirs, and ponds. Excessive nutrients, such as nitrogen and phosphorus, lead to eutrophication, a condition that can include low oxygen levels, noxious algal blooms, and fish kills. Since eutrophication is a condition that manifests itself differently in different systems, there is not a criterion variable with a clear threshold that can be used to set the criterion level. This dissertation presents an approach to address the question: How should States and Tribes choose nutrient criteria to determine eutrophication-related impairments of the designated use? To address this question I used a combination of water quality modeling and decision analysis to determine the optimal nutrient criterion variables and levels. To choose criterion variables that are predictive of the designated use, I utilized statistical models (structural equation models, multiple regression, and binomial regression model) to link the measured water quality variables to expert elicited categories of eutrophication and the designated uses. These models were applied successfully to single waterbodies, the Kissimmee Chain-of-Lakes region, and the State of North Carolina to assess which candidate criterion variables were the most predictive. Additionally, the models indicated that the variables that were most predictive of eutrophication were also the most predictive of the designated use. Using the predictive nutrient criteria variables, I applied a decision-analytic approach to nutrient criteria setting in North Carolina. I developed a nutrient criteria value model that included two submodels, a water quality model and a multiattribute value model. The submodels were parameterized using a combination of water quality data, expert elicitation data, and utility assessments. The outcome of the nutrient criteria value model is the overall expected value for a criterion level choice; the optimal criterion level would be the choice that maximized the expected value. Using the preferences of North Carolina environmental decision-makers and a total phosphorus criterion variable, the optimal criterion level was between 0.03 mg/L and 0.07 mg/L. Ultimately, I hope this research will establish methodology used to set appropriate water quality criteria. / Dissertation