El problema de encontrar condiciones robustas al efecto de factores no controlados es un tema que interesa enormemente a las empresas ya que es una característica que demanda el mercado. Existen básicamente dos métodos para estudiar el problema: El que se basa en el método propuesto por G. Taguchi a comienzos de los 80's con el que se aproxima la variabilidad a partir de matrices producto y se seleccionan las condiciones robustas minimizando la respuesta, o el que parte de una matriz más económica que permite estimar un modelo para la respuesta Y en función de los factores de control y ruido, y estudia las condiciones robustas a partir de las interacciones entre los factores ruido y los factores de control. Aunque en un principio cabrían esperar resultados muy similares analizando un mismo problema por las dos vías hemos encontrado ejemplos donde las conclusiones son muy dispares y por ello nos hemos planteado este trabajo de investigación para encontrar las causas de estas diferencias.El trabajo de investigación lo hemos iniciado estudiando la naturaleza de las superficies asociadas a la variabilidad provocada por factores ruido realizando el estudio de forma secuencial aumentando el número de factores ruido. Hemos demostrado que independientemente de que la métrica seleccionada sea s2(Y), s(Y) o lo(s(Y)) las superficies difícilmente podrán ser aproximadas por polinomios de primer orden en los factores de control llegando a la conclusión de que algunas de las estrategias habituales que los experimentadores utilizan en la práctica difícilmente llevan a un buen conocimiento de esta superficie. Por ejemplo no es adecuado colocar un diseño 2k-p de Resolución III en los factores de control en una matriz producto siendo recomendables diseños de Resolución IV con puntos centrales.A continuación se han supuesto dos fuentes de variación en la respuesta debidas a ruido, fuentes desconocidas para el experimentador, y se ha estudiado la sensibilidad de los dos métodos para recoger estas oportunidades de reducción de la variabilidad demostrándose que el modelo para métricas resumen está más preparado para recoger todas las fuentes de variación que el modelo a partir de métricas no-resumen, el cual es muy sensible a la estimación del modelo de Y.Por último se ha investigado sobre los errores más comunes a la hora de seleccionar las condiciones robustas a partir de gráficos.

The main objective of this thesis is to investigate risk neutral and risk averse approaches to multistage stochastic programming with applications to hydrothermal operation planning problems. The purpose of hydrothermal system operation planning is to define an operation strategy which, for each stage of the planning period, given the system state at the beginning of the stage, produces generation targets for each plant. This problem can be formulated as a large scale multistage stochastic linear programming problem. The energy rationing that took place in Brazil in the period 2001/2002 raised the question of whether a policy that is based on a criterion of minimizing the expected cost (i.e. risk neutral approach) is a valid one when it comes to meet the day-to-day supply requirements and taking into account severe weather conditions that may occur. The risk averse methodology provides a suitable framework to remedy these deficiencies. This thesis attempts to provide a better understanding of the risk averse methodology from the practice perspective and suggests further possible alternatives using robust optimization techniques. The questions investigated and the contributions of this thesis are as follows. First, we suggest a multiplicative autoregressive time series model for the energy inflows that can be embedded into the optimization problem that we investigate. Then, computational aspects related to the stochastic dual dynamic programming (SDDP) algorithm are discussed. We investigate the stopping criteria of the algorithm and provide a framework for assessing the quality of the policy. The SDDP method works reasonably well when the number of state variables is relatively small while the number of stages can be large. However, as the number of state variables increases the convergence of the SDDP algorithm can become very slow. Afterwards, performance improvement techniques of the algorithm are discussed. We suggest a subroutine to eliminate the redundant cutting planes in the future cost functions description which allows a considerable speed up factor. Also, a design using high performance computing techniques is discussed. Moreover, an analysis of the obtained policy is outlined with focus on specific aspects of the long term operation planning problem. In the risk neutral framework, extreme events can occur and might cause considerable social costs. These costs can translate into blackouts or forced rationing similarly to what happened in 2001/2002 crisis. Finally, issues related to variability of the SAA problems and sensitivity to initial conditions are studied. No significant variability of the SAA problems is observed. Second, we analyze the risk averse approach and its application to the hydrothermal operation planning problem. A review of the methodology is suggested and a generic description of the SDDP method for coherent risk measures is presented. A detailed study of the risk averse policy is outlined for the hydrothermal operation planning problem using different risk measures. The adaptive risk averse approach is discussed under two different perspectives: one through the mean-$avr$ and the other through the mean-upper-semideviation risk measures. Computational aspects for the hydrothermal system operation planning problem of the Brazilian interconnected power system are discussed and the contributions of the risk averse methodology when compared to the risk neutral approach are presented. We have seen that the risk averse approach ensures a reduction in the high quantile values of the individual stage costs. This protection comes with an increase of the average policy value - the price of risk aversion. Furthermore, both of the risk averse approaches come with practically no extra computational effort and, similarly to the risk neutral method, there was no significant variability of the SAA problems. Finally, a methodology that combines robust and stochastic programming approaches is investigated. In many situations, such as the operation planning problem, the involved uncertain parameters can be naturally divided into two groups, for one group the robust approach makes sense while for the other the stochastic programming approach is more appropriate. The basic ideas are discussed in the multistage setting and a formulation with the corresponding dynamic programming equations is presented. A variant of the SDDP algorithm for solving this class of problems is suggested. The contributions of this methodology are illustrated with computational experiments of the hydrothermal operation planning problem and a comparison with the risk neutral and risk averse approaches is presented. The worst-case-expectation approach constructs a policy that is less sensitive to unexpected demand increase with a reasonable loss on average when compared to the risk neutral method. Also, we comp are the suggested method with a risk averse approach based on coherent risk measures. On the one hand, the idea behind the risk averse method is to allow a trade off between loss on average and immunity against unexpected extreme scenarios. On the other hand, the worst-case-expectation approach consists in a trade off between a loss on average and immunity against unanticipated demand increase. In some sense, there is a certain equivalence between the policies constructed using each of these methods.

This dissertation studies models for locating facilities in time varying demand environments. We describe the characteristics of the time varying demand that motivate the analysis of our location models in terms of total demand and the change in value and location of the demand of each customer. The first part of the dissertation is devoted to the dynamic location model, which determines the optimal time and location for establishing capacitated facilities when demand and cost parameters are time varying. This model minimizes the total cost over a discrete and finite time horizon for establishing, operating, and closing facilities, including the transportation costs for shipping demand from facilities to customers. The model is solved using Lagrangian relaxation and Benders? decomposition. Computational results from different time varying total demand structures demonstrate, empirically, the performance of these solution methods. The second part of the dissertation studies two location models where relocation of facilities is not allowed and the objective is to determine the optimal location of capacitated facilities that will have a good performance when demand and cost parameters are time varying. The first model minimizes the total cost for opening and operating facilities and the associated transportation costs when demand and cost parameters are time varying. The model is solved using Benders? decomposition. We show that in the presence of high relocation costs of facilities (opening and closing costs), this model can be solved as a special case by the dynamic location model. The second model minimizes the maximum regret or opportunity loss between a robust configuration of facilities and the optimal configuration for each time period. We implement local search and simulated annealing metaheuristics to efficiently obtain near optimal solutions for this model.

A gas turbine engine design process was developed for the design of a common core engine family. The process considers initial and projected variant engine applications, likely technology maturation, and various sources of uncertainty when making initial core design considerations. A physics based modeling and simulation environment was developed to enforce geometric core commonality between the core defining design engine and a common core variant engine. The environment also allows for upgrade options and technology to be infused into the variant engine design. The relationships established in the model enable commonality to be implicitly enforced when performing simultaneous design space explorations of the common core design and all corresponding variant engine designs. A robust design simulation process was also developed, enabling probabilistic surrogate model representations of the common core engine family design space to be produced. The probabilistic models provide confidence interval performance estimates with a single function call for an inputted set of core and variant design settings and the uncertainty distribution shape parameter settings representative of an uncertainty scenario of interest. The unique form of the probabilistic surrogate models enables large numbers of common core engine family applications to be considered simultaneously, each being simulated under a unique uncertainty scenario. Implications of core design options can be instantaneously predicted for all engine applications considered, allowing for favorable common core design regions to be identified in a highly efficient manner.

The term sustainable agriculture may be formulated, but not yet practically integrated in agriculture. This thesis investigates the organic farmers´ ideas and experiences of what they consider sustainable or not sustainable in agriculture. Using unstructured phone interviews and "walk-alongs" with KRAV-farmers in Kristianstad, I have sought to understand their ideas and experiences, inspired by the phenomenological approach. The thesis communicates the experiences of organic farmers of sustainable agriculture based on an explicit role as stewards of the same. How come they express themselves and act the way they do? Why are these issues important and how do they relate to each other? The result, using the three dimensions of economical, ecological and social sustainability, is presented. How farmers experience profitability, eco-awareness and influence in their stewardship are important. The overlapping areas for sustainability describe the need of fair terms in socioeconomic terms. Agroecologically, the stewards need to experience the work to be practically feasible, both financially and ecologically. Socioecologically, their stewardship becomes more acceptable within an eco-aware market, which adds to their individual creation of meaning. Even though there are ideas and experiences of what sustainable agriculture includes, this does not necessarily mean that this is what the farmers find in their work. In the eyes of these farmers, their experiences need to be more just, feasible and acceptable for sustainability. How farmers continue to handle complex choices in agriculture for economic, ecological and social sustainability is interesting; not only for the farmers themselves, but also in a societal perspective for long-term domestic food security. What they see as sustainable depends on the choices of other stakeholders and how the farmers themselves formulate goals and purpose with regard to their own farming. They argue that one thing leads to another, which the thesis gives plenty of practical examples of. The thesis should be seen as a normative contribution to the public debate about what is sustainable, listening to the voices of organic farmers.

Orientador: Rodrigo Cardim / Resumo: Neste trabalho são apresentados uma série de resultados relacionados com as técnicas de controle para sistemas lineares chaveados incertos que asseguram índices de desempenho e custos garantidos no projeto. Inicialmente a técnica abordada para este estudo consiste na utilização das desigualdades de Lyapunov-Metzler e as propriedades dos sistemas Estritamente Reais Positivos (ERP). São abordados os sistemas Lyapunov-Metzler-ERP (LMERP), que permitem o desenvolvimento de um método de projeto de estabilização para sistemas que apresentam comutação e incertezas no modelo, usando para isto a realimentação do vetor de estado. A análise de estabilidade é descrita por meio de Desigualdades Matriciais Lineares (em inglês: Linear Matrix Inequalities), LMIs, que, quando factíveis, são facilmente resolvidas por meio de ferramentas disponíveis de programação convexa. Neste trabalho trata-se também da síntese via realimentação de estado com chaveamento no ganho que assegura o critério de desempenho Hoo. Para a validação das estratégias de controle mencionadas foram realizadas simulações e experimentos práticos em um sistema de suspensão ativa de bancada e em um sistema ball balancer, equipamentos fabricados pela Quanser. Os resultados comprovam a eficácia dos método propostos tanto nas simulações quanto nos testes realizados em bancada. / Mestre

The sequence of a polypeptide chain determines its structure which in turns determines its function. A protein is stabilized by multiple forces; hydrophobic interaction, electrostatic interactions and hydrogen bond formation between residues. While the above forces are non-covalent in nature the protein structure is also stabilized by disulfide bonds. Structural features such as naturally occurring cavities in proteins also affect its stability. Studying factors which affect a protein’s structural stability helps us understand complex sequence-structure-function relationships, the knowledge of which can be applied in areas such as protein engineering. The work presented in this thesis deals with various and diverse aspects of protein structure. Chapter 1 gives an overall introduction on the topics studied in this thesis. Chapter 2 focuses on a unique, non-regular, structural feature of proteins, viz. protein cavities. Cavities directly affect the packing density of the protein. It has been shown that large to small cavity creating mutations destabilize the protein with the extent of destabilization being proportional to the size of cavity created. On the other hand, small to large cavity filling mutations have been shown to increase protein stability. Tools which analyze protein cavities are thus important in studies pertaining to protein structure and stability. The chapter presents two methods which detect and calculate cavity volumes in proteins. The first method, DEPTH 2.0, focuses on accurate detection and volume calculation of cavities. The second method, ROBUSTCAVITIES, focuses on detection of biologically relevant cavities in proteins. We then study another aspect of protein structure – the disulfide bond. Disulfide bonds confer stability to the protein by decreasing the entropy of the unfolded state. Previous studies which attempted to engineer disulfides in proteins have shown mixed results. Previously, disulfide bonds in individual secondary structures were characterized. Analysis of disulfides in α-helices and antiparallel β-strands yielded important common features of such bonds. In Chapter 3 we present a review of these studies. We then use MODIP; a tool that identifies amino acid pairs which when mutated to cysteines will most likely form a disulfide bond, to analyze disulfide bonds in parallel β-strands. A direct way to analyze sequence-structure relationships is via mutating individual residues, evaluating the effect on stability and activity of the protein and inferring its effect on protein structure. Saturation mutagenesis libraries, where all possible mutations are made at every position in the protein contain a huge amount of information pertaining to the effect of mutations on structure. Making such libraries and screening them has been an extremely resource intensive process. We combine a fast inverse PCR based method to rapidly generate saturation mutagenesis libraries with the power of deep sequencing to derive phenotypes of individual mutants without any large scale screening. In Chapter 4 we present an Illumina data analysis pipeline which analyzes sequencing data from a saturation mutagenesis library, and derives individual mutant phenotypes with high confidence. In Chapter 5 we apply the insights derived from structure-function studies and apply it to the problem of protein engineering, specifically immunogen design. The Human Immunodeficiency Virus adopts various strategies to evade the host immune system. Being able to display the conserved epitopes which elicit a broadly neutralizing response is the first step towards an effective vaccine. Grafting such an epitope onto a foreign scaffold will mitigate some of the key HIV defenses. We develop a computational protocol which grafts the broadly neutralizing antibody b12 epitope on scaffolds selected from the PDB. This chapter also describes the only experimental work presented in this thesis viz. cloning, expressing and screening the epitope-scaffolds using Yeast Surface Display. Our epitope-scaffolds show modest but specific binding. In a bid to improve binding, we make random mutant libraries of the epitope-scaffolds and screen them for better binders using FACS. This work is on-going and we aim to purify our epitope-scaffolds, characterize them biophysically and eventually test their efficacy as immunogens.

Made available in DSpace on 2016-06-02T19:50:26Z (GMT). No. of bitstreams: 1 6825.pdf: 8500191 bytes, checksum: 6105a0900d48c9c1c58657efd7bc22ac (MD5) Previous issue date: 2015-12-16 / The tactical management of cash flow is critical in financial management of a company or organization. Several mathematical models for planning cash flow have been proposed in recent decades. Most of the models are deterministic and initially treated as an extension of the economic order quantity. This thesis addresses the cash management problem from the perspective of optimization models present in the Operations Research literature. The aim is to study, develop and apply formulations based on mathematical programming and network flows, considering uncertainties in parameters, to support the decisions involved in managing the cash flow. A case study was developed in a typical company of the stationery sector to analyze the suitability and potential of the proposed approaches for companies of this sector. For that, this thesis implement robust optimization and stochastic programming to address the parameters uncertainties in the problem of maximizing the available financial resources at the end of a multi-period and finite planning horizon of the company's cash flow. The proposed approaches are based on a deterministic model which uses a network flow to maximize the cash flow return at the end of the period. For the treatment of uncertainties in the parameters that define the flow of financial resources in time are used the robust optimization approach of worst case interval and the stochastic programming approach risk neutral, minimax with regret and conditional value-at-risk. There were no other studies in the literature following this line of research. As shown in this thesis the proposed approaches can generated promising results for the management of cash flow in companies of the stationery sector and others, with significant contributions in financial decision-making department, particularly for the treatment of uncertainties in the parameters of the cash flow. / O gerenciamento do fluxo de caixa tático é fundamental na gestão financeira de uma empresa ou organização. Vários modelos matemáticos para planejar o fluxo de caixa foram propostos nas últimas décadas. Na sua maioria, os modelos são determinísticos e, inicialmente, tratados como uma extensão da fórmula do lote econômico de compra. Esta tese aborda o problema da gestão do caixa sob a ótica de modelos de otimização presentes na literatura da Pesquisa Operacional. O objetivo é estudar, desenvolver e aplicar formulações baseadas em programação matemática e fluxos em rede, considerando incertezas nos parâmetros, para apoiar as decisões envolvidas no gerenciamento do fluxo de caixa. Um estudo de caso é desenvolvido numa empresa típica do setor de material escolar, para analisar a adequação e o potencial das abordagens propostas em empresas deste setor. Para tal, são utilizados métodos de otimização robusta e programação estocástica para tratar as incertezas nos parâmetros do problema de maximização dos recursos financeiros disponíveis no final de um horizonte de planejamento multi-período e finito do caixa da empresa. As abordagens propostas são baseadas num modelo determinístico, que utiliza uma rede de fluxos para maximizar o retorno do caixa no final do período considerado. Para o tratamento das incertezas presentes nos parâmetros que definem os fluxos de recursos no tempo, são utilizadas a abordagem de otimização robusta de análise de pior caso intervalar e a abordagem de programação estocástica de dois estágios com recurso neutra ao risco e de aversão ao risco minimax com arrependimento e valor em risco condicional. Não foram encontrados outros estudos na literatura seguindo esta linha de pesquisa. Conforme mostrado nesta tese, as abordagens propostas podem gerar resultados promissores para a gestão do fluxo de caixa de empresas de material escolar e outros, com contribuições significativas nas tomadas de decisões de um gestor financeiro, principalmente quanto ao tratamento das incertezas nos parâmetros do fluxo de caixa.

Submitted by IVAN FRANCISCO YUPANQUI TELLO null (ivan.yupanqui.tello@hotmail.com) on 2017-06-28T18:37:59Z No. of bitstreams: 1 minha dissertacao.pdf: 4687608 bytes, checksum: 8a9fc873657ce7c21593f7e3653e4b0c (MD5) / Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-06-28T20:46:09Z (GMT) No. of bitstreams: 1 tello_ify_me_ilha.pdf: 4687608 bytes, checksum: 8a9fc873657ce7c21593f7e3653e4b0c (MD5) / Made available in DSpace on 2017-06-28T20:46:09Z (GMT). No. of bitstreams: 1 tello_ify_me_ilha.pdf: 4687608 bytes, checksum: 8a9fc873657ce7c21593f7e3653e4b0c (MD5) Previous issue date: 2017-06-20 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Neste trabalho são apresentados uma série de resultados relacionados com as técnicas de controle para sistemas lineares chaveados incertos que asseguram índices de desempenho e custos garantidos no projeto. Inicialmente a técnica abordada para este estudo consiste na utilização das desigualdades de Lyapunov-Metzler e as propriedades dos sistemas Estritamente Reais Positivos (ERP). São abordados os sistemas Lyapunov-Metzler-ERP (LMERP), que permitem o desenvolvimento de um método de projeto de estabilização para sistemas que apresentam comutação e incertezas no modelo, usando para isto a realimentação do vetor de estado. A análise de estabilidade é descrita por meio de Desigualdades Matriciais Lineares (em inglês: Linear Matrix Inequalities), LMIs, que, quando factíveis, são facilmente resolvidas por meio de ferramentas disponíveis de programação convexa. Neste trabalho trata-se também da síntese via realimentação de estado com chaveamento no ganho que assegura o critério de desempenho Hoo. Para a validação das estratégias de controle mencionadas foram realizadas simulações e experimentos práticos em um sistema de suspensão ativa de bancada e em um sistema ball balancer, equipamentos fabricados pela Quanser. Os resultados comprovam a eficácia dos método propostos tanto nas simulações quanto nos testes realizados em bancada. / This work presents a series of results related to the control techniques for uncertain switched linear systems that ensure performance indicators and guaranteed cost in the design. Initially the technique discussed in this study is the use of Lyapunov-Metzler Inequalities and properties of Strictly Positive Real Systems (SPR), so the Lyapunov-Metzler-SPR systems (LMSRP) are revised, which allow the development of a method of stabilization for systems that have switching and uncertainties in the model, using for this the state feedback. The stability analysis is described by Linear Matrix Inequalities, LMIs, that when are feasible, these are easily solved through tools available in convex programming literature. We also deal with the synthesis via state feedback with switching in the gain that ensures the performance criterion Hoo. In order to validate the proposed strategy simulations and experiments were performed on a bench active suspension system and a ball balancer system, equipments manufactured by Quanser. The results prove the effectiveness of the proposed method both in simulations and in bench tests.

Made available in DSpace on 2016-08-17T14:53:25Z (GMT). No. of bitstreams: 1 dissertacao Danubia.pdf: 4153198 bytes, checksum: f8dd2d9ab5e8fbfa00744bcff5dce73b (MD5) Previous issue date: 2013-09-30 / In this master thesis, a robust fuzzy digital PID control methodology based on gain and phase margins specifications, is proposed. A mathematical formulation, based on gain and phase margins specifications, the Takagi-Sugeno fuzzy model of the plant to be controlled, the structure of the digital PID controller and the time delay uncertain system, was developed. From input and output data of the plant, the fuzzy clustering Fuzzy C-Means (FCM) algorithm estimates the antecedent parameters (operation areas ) and the rules number of Takagi-Sugeno fuzzy model. The least squares algorithm provides the consequent parameters linear submodels. A multiobjective genetic strategy is defined to tune the fuzzy digital PID controller parameters, so the gain and phase margins specified to the fuzzy control system are get. An analysis of necessary and sufficient conditions for fuzzy digital PID controller design with robust stability, with the proposal of the two theorems are presented. The digital fuzzy PID controller was implemented on a platform designed for monitoring and control in real time, based on CompactRIO and LabVIEW 9073, National Instruments, of the Laboratory of Computational Intelligence Applied to Technology (ICAT/DEE/IFMA), applying the temperature control of a thermal plant. Experimental results show the efficiency of the proposed methodology, through tracking of the reference and the gain and phase margins keeping closed of the specified ones. / Nesta dissertação é proposta uma metodologia para projeto de controle PID digital nebuloso robusto baseado nas especificações das margens de ganho e fase. É desenvolvida uma formulação matemática, baseada nas especificações das margens de ganho e fase, no modelo nebuloso Takagi-Sugeno da planta a ser controlada, na estrutura do controlador PID digital e o atraso de tempo do sistema incerto. A partir dos dados de entrada e saída da planta, o algoritmo de agrupamento nebuloso Fuzzy C-Means (FCM), estima os parâmetros do antecedente (regiões de operação) e o número de regras do modelo nebuloso Takagi-Sugeno. O algoritmo de mínimos quadrados fornece os parâmetros dos submodelos lineares do consequente. Uma estratégia genética multiobjetiva é utilizada para encontrar os parâmetros do controlador PID digital nebuloso, de modo que as margens de ganho e fase especificadas para o sistema de controle nebuloso sejam alcançadas. Uma análise das condições necessárias e suficientes para o projeto do controlador PID digital nebuloso com estabilidade robusta, a partir da proposta de dois teoremas, é apresentada. O controlador PID digital nebuloso projetado foi implementado numa plataforma para supervisão e controle em tempo real, baseada no CompactRIO 9073 e no software LabVIEW, da National Instruments, do Laboratório de Inteligência Computacional Aplicada à Tecnologia (ICAT/DEE/IFMA), com aplicação ao controle de temperatura de uma planta térmica. Resultados experimentais mostram a eficiência da metodologia proposta, uma vez que a trajetória de referência é seguida e as margens de ganho e fase permanecem próximas às especificadas.