Multivariate adaptive regression spline (MARS) denotes a modern methodology from statistical learning which is very important in both classification and regression, with an increasing number of applications in many areas of science, economy and technology. MARS is very useful for high dimensional problems and shows a great promise for fitting nonlinear multivariate functions. MARS technique does not impose any particular class of relationship between the predictor variables and outcome variable of interest. In other words, a special advantage of MARS lies in its ability to estimate the contribution of the basis functions so that both the additive and interaction effects of the predictors are allowed to determine the response variable. The function fitted by MARS is continuous, whereas the one fitted by classical classification methods (CART) is not. Herewith, MARS becomes an alternative to CART. The MARS algorithm for estimating the model function consists of two complementary algorithms: the forward and backward stepwise algorithms. In the first step, the model is built by adding basis functions until a maximum level of complexity is reached. On the other hand, the backward stepwise algorithm is began by removing the least significant basis functions from the model. In this study, we propose not to use the backward stepwise algorithm. Instead, we construct a penalized residual sum of squares (PRSS) for MARS as a Tikhonov regularization problem, which is also known as ridge regression. We treat this problem using continuous optimization techniques which we consider to become an important complementary technology and alternative to the concept of the backward stepwise algorithm. In particular, we apply the elegant framework of conic quadratic programming which is an area of convex optimization that is very well-structured, herewith, resembling linear programming and, hence, permitting the use of interior point methods. The boundaries of this optimization problem are determined by the multiobjective optimization approach which provides us many alternative solutions. Based on these theoretical and algorithmical studies, this MSc thesis work also contains applications on the data investigated in a T&Uuml / BiTAK project on quality control. By these applications, MARS and our new method are compared.

Made available in DSpace on 2014-12-17T15:48:07Z (GMT). No. of bitstreams: 1 RomeritoCA_DISSERT.pdf: 1649773 bytes, checksum: 9a9fd0e3782657fe6d014020cdc8fb90 (MD5) Previous issue date: 2013-02-01 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / This work presents a algorithmic study of Multicast Packing Problem considering a multiobjective approach. The first step realized was an extensive review about the problem. This review serverd as a reference point for the definition of the multiobjective mathematical model. Then, the instances used in the experimentation process were defined, this instances were created based on the main caracteristics from literature. Since both mathematical model and the instances were definined, then several algoritms were created. The algorithms were based on the classical approaches to multiobjective optimization: NSGA2 (3 versions), SPEA2 (3 versions). In addition, the GRASP procedures were adapted to work with multiples objectives, two vesions were created. These algorithms were composed by three recombination operators(C1, C2 e C3), two operator for build solution, a mutation operator and a local search procedure. Finally, a long experimentation process was performed. This process has three stages: the first consisted of adjusting the parameters; the second was perfomed to indentify the best version for each algorithm. After, the best versions for each algorithm were compared in order to identify the best algorithm among all. The algorithms were evaluated based on quality indicators and Hypervolume Multiplicative Epsilon / O presente trabalho apresenta um estudo algor?tmico do Multicast Packing Problem levando em considera??o uma abordagem multiobjetivo. Para tal, faz-se uma extensa revis?o sobre o problema em quest?o. Esta revis?o serviu como ponto de refer?ncia para defini??o de um modelo matem?tico multiobjetivo, tendo em vista que n?o h? na literatura nenhum trabalho que tenha tratado o tema neste aspecto. Em seguida, define-se os casos de teste utilizados no processo de experimenta??o dos algoritmos. Uma vez que tanto modelo matem?tico multiobjetivo quanto os casos de teste foram criados, ent?o desenvolve-se v?rios algoritmos com base nas abordagens cl?ssicas para problemas de otimiza??o multiobjetivo: NSGA2 (3 vers?es) e SPEA2 (3 vers?es). Al?m disso, adaptou-se a metaheur?stica GRASP (2 vers?es) para aplica??o considerando o modelo proposto. Estes algoritmos foram compostos por tr?s operadores de recombina??o (C1, C2, C3), dois operadores de constru??o de solu??o, um operador de muta??o e um operador de busca local. Por fim, um extenso processo de experimenta??o dos algoritmos ? realizado. Este processo possui tr?s etapas: a primeira etapa consistiu de ajustar os par?metros que cada algoritmo necessita, neste caso o ajuste de par?metro foi realizado para todas as vers?es do SPEA2, NSGA2 e GRASP; A segunda etapa consistiu de verificar, para cada algoritmo, qual a melhor vers?o. Por fim, as melhores vers?es de cada algoritmo, no total 3 vers?es, foram comparadas entre si visando identificar qual o melhor algoritmo dentre todos. Os algoritmos foram avaliados com base nos indicadores de qualidade Hypervolume e Epsilon Multiplicativo. Os resultados dos experimentos foram avaliados atrav?s de testes estat?sticos n?o-param?tricos (teste de Mann-Whitney e teste de Friedman). A avalia??o dos resultados foi favor?ravel ao NSGA2-C2 segundo a metodologia de avalia??o utilizada

Submitted by Leonardo Cavalcante (leo.ocavalcante@gmail.com) on 2018-06-11T11:34:10Z No. of bitstreams: 1 Arquivototal.pdf: 1995596 bytes, checksum: bfcc1e1f3a77514dcbf7a8e4f5e4701b (MD5) / Made available in DSpace on 2018-06-11T11:34:10Z (GMT). No. of bitstreams: 1 Arquivototal.pdf: 1995596 bytes, checksum: bfcc1e1f3a77514dcbf7a8e4f5e4701b (MD5) Previous issue date: 2017-02-16 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / The problem in investment portfolio selection consists in the allocation of resources to a finite number of assets, aiming, in its classic approach, to overcome a trade-off between the risk and expected return of the portfolio. This problem is one of the most important topics targeted at today’s financial and economic issues. Since the pioneering works of Markowitz, the issue is treated as an optimisation problem with the two aforementioned objectives. However, in recent years, various restrictions and additional risk measurements were identified in the literature, such as, for example, cardinality restrictions, minimum transaction lot and asset pre-selection. This practice aims to bring the issue closer to the reality encountered in financial markets. In that regard, this paper proposes a metaheuristic called Particle Swarm for the optimisation of several PSPs, in such a way that allows the resolution of the problem considering a set of restrictions chosen by the investor. / O problema de seleção de carteiras de investimentos (PSP) consiste na alocação de recursos a um número finito de ativos, objetivando, em sua abordagem clássica, superar um trade-off entre o retorno esperado e o risco da carteira. Tal problema ´e uma das temáticas mais importantes voltadas a questões financeiras e econômicas da atualidade. Desde os pioneiros trabalhos de Markowitz, o assunto é tratado como um problema de otimização com esses dois objetivos citados. Entretanto, nos últimos anos, diversas restrições e mensurações de riscos adicionais foram consideradas na literatura, como, por exemplo, restrições de cardinalidade, de lote mínimo de transação e de pré-seleção de ativos. Tal prática visa aproximar o problema da realidade encontrada nos mercados financeiros. Neste contexto, o presente trabalho propõe uma meta-heurística denominada Adaptive Non-dominated Sorting Multiobjective Particle Swarm Optimization para a otimização de vários problemas envolvendo PSP, de modo que permita a resolução do problema considerando um conjunto de restri¸c˜oes escolhidas pelo investidor.

L'amélioration de la gestion des ressources naturelles est nécessaire pour répondre aux nombreux enjeux liés à leur exploitation. Ce travail propose une méthodologie d'optimisation de leur gestion, appliquée au cas du cuivre en France. Quatre critères permettant de juger les stratégies de gestion ont été retenus : le coût, les impacts environnementaux, la consommation énergétique et les pertes de ressources. La première étape de cette méthodologie est l'analyse de la situation actuelle, grâce à une modélisation du cycle français du cuivre de 2000 à 2009. Cet examen a montré que la France importe la quasi-totalité de ses besoins sous forme de cuivre raffiné, et a une industrie de recyclage peu développée. Suite à ces premiers résultats, la problématique du traitement des déchets de cuivre, et notamment de leur recyclage, a été étudiée. Une stratégie de modélisation des flux recyclés, basée sur la construction de flowsheets, a été développée. La formulation mathématique générale du problème a ensuite été définie : il s'agit d'un problème mixte, non-linéaire et a priori multiobjectif, qui a une contrainte égalité forte (la conservation de la masse). Une étude des méthodes d'optimisation a conduit à choisir un algorithme génétique (AG). Une alternative a également été envisagée pour résoudre le problème multiobjectif par programmation linéaire en le linéarisant "sous contrainte". Ce travail a mis en évidence la nécessité de développer une filière de recyclage efficace des déchets électriques et électroniques en France. Il a de plus montré que le cuivre contenu dans les déchets ne permet pas de couvrir la demande et qu'il est nécessaire d'importer du cuivre, de préférence sous forme de débris. / Improving the natural resources management is necessary to address the many issues related to their exploitation. This work proposes an optimization methodology for their management, applied to the case of copper in France. Four criteria are identified to assess management strategies: cost, environmental impacts, energy consumption and resource losses. The first step of this methodology is the analysis of the current situation, by modelling the French copper cycle from 2000 to 2009. This analysis showed that France imports almost all of its needs as refined copper, and has an underdeveloped recycling industry. Following these initial results, the problematic of copper wastes, including recycling, has been investigated. A recycled flow modelling strategy has been developed, based on the construction of flowsheets. The general mathematical formulation of the problem is then defined. It is a non-linear, mixed and a priori multiobjective problem, with a strong equality constraint (mass conservation). A review of optimization methods has led to choose a genetic algorithm (GA). An alternative was also proposed to solve the multiobjective problem with linear programming, by linearizing it under constraint. This work has highlighted the necessity of developing an effective recycling field of wastes from electric and electronic equipment in France. It also showed that the copper contained in wastes does not meet the demand, so that France needs to import copper, preferably as scraps.

Nous étudions la distillation extractive continue de mélanges azéotropiques à temperature de bulle minimale avec un entraineur lourd (classe 1.0-1a) avec comme exemples les mélanges acétone-méthanol avec l’eau et DIPE-IPA avec le 2-méthoxyethanol. Le procédé inclut les colonnes de distillation extractive et de régénération de l’entraineur en boucle ouverte et en boucle fermée. Une première stratégie d’optimisation consiste à minimiser la fonction objectif OF en cherchant les valeurs optimales du débit d’entraineur FE, les positions des alimentations en entraineur et en mélange NFE, NFAB, NFReg, les taux de reflux R1, R2 et les débits de distillat de chaque colonne D1, D2. OF décrit la demande en énergie par quantité de distillat et tient compte des différences de prix entre les utilités chaudes et froides et entre les deux produits. La deuxième stratégie est une optimisation multiobjectif qui minimise OF, le coût total annualisé (TAC) et maximise deux nouveaux indicateurs thermodynamiques d’efficacité de séparation extractive totale Eext et par plateau eext. Ils décrivent la capacité de la section extractive à séparer le produit entre le haut et le bas de la section extractive. L’analyse thermodynamique des réseaux de courbes de résidu ternaires RCM et des courbes d’isovolatilité montre l’intérêt de réduire la pression opératoire dans la colonne extractive pour les séparations de mélanges 1.0-1a. Une pression réduite diminue la quantité minimale d’entraineur et accroît la volatilité relative du mélange binaire azéotropique dans la région d’opération de la colonne extractive. Cela permet d’utiliser un taux de reflux plus faible et diminue la demande énergétique. La première stratégie d’optimisation est conduite avec des contraintes sur la pureté des produits avec les algorithmes SQP dans les simulateurs Aspen Plus ou Prosim Plus en boucle ouverte. Les variables continues optimisées sont : R1, R2 et FE (étape 1). Une étude de sensibilité permet de trouver les valeurs de D1, D2 (étape 2) et NFE, NFAB, NFReg (étape 3), tandis l’étape 1 est faite pour chaque jeu de variables discrètes. Enfin le procédé est resimulé en boucle fermée et TAC, Eext et eext sont calculés (étape 4). Les bilans matières expliquent l’interdépendance des débits de distillats et des puretés des produits. Cette optimisation permet de concevoir des procédés avec des gains proches de 20% en énergie et en coût. Les nouveaux procédés montrent une amélioration des indicateurs Eext et eext. Afin d’évaluer l’influence de Eext et eext sur la solution optimale, la seconde optimisation multiobjectif est conduite. L’algorithme génétique est peu sensible à l’initialisation, permet d’optimiser les variables discrètes N1, N2 et utilise directement le shéma de procédé en boucle fermée. L’analyse du front de Pareto des solutions met en évidence l’effet de FE/F et R1 sur TAC et Eext. Il existe un Eext maximum (resp. R1 minimum) pour un R1 donné (resp. Eext). Il existe aussi un indicateur optimal Eext,opt pour le procédé optimal avec le plus faible TAC. Eext,opt ne peut pas être utilisé comme seule fonction objectif d’optimisation mais en complément des autres fonctions OF et TAC. L’analyse des réseaux de profils de composition extractive explique la frontière du front de Pareto et pourquoi Eext augmente lorsque FE diminue et R1 augmente, le tout en lien avec le nombre d’étage. Visant à réduire encore TAC et la demande énergétique nous étudions des procédés avec intégration énergétique double effet (TEHI) ou avec des pompes à chaleur (MHP). En TEHI, un nouveau schéma avec une intégration énergétique partielle PHI réduit le plus la demande énergétique. En MHP, la recompression partielle des vapeurs VRC et bottom flash partiel BF améliorent les performances de 60% et 40% respectivement. Au final, le procédé PHI est le moins coûteux tandis que la recompression totale des vapeurs est la moins énergivore. / We study the continuous extractive distillation of minimum boiling azeotropic mixtures with a heavy entrainer (class 1.0-1a) for the acetone-methanol with water and DIPE-IPA with 2-methoxyethanol systems. The process includes both the extractive and the regeneration columns in open loop flowsheet and closed loop flowsheet where the solvent is recycled to the first column. The first optimization strategy minimizes OF and seeks suitable values of the entrainer flowrate FE, entrainer and azeotrope feed locations NFE, NFAB, NFReg, reflux ratios R1, R2 and both distillates D1, D2. OF describes the energy demand at the reboiler and condenser in both columns per product flow rate. It accounts for the price differences in heating and cooling energy and in product sales. The second strategy relies upon the use of a multi-objective genetic algorithm that minimizes OF, total annualized cost (TAC) and maximizes two novel extractive thermodynamic efficiency indicators: total Eext and per tray eext. They describe the ability of the extractive section to discriminate the product between the top and to bottom of the extractive section. Thermodynamic insight from the analysis of the ternary RCM and isovolatility curves shows the benefit of lowering the operating pressure of the extractive column for 1.0-1a class separations. A lower pressure reduces the minimal amount of entrainer and increases the relative volatility of original azeotropic mixture for the composition in the distillation region where the extractive column operates, leading to the decrease of the minimal reflux ratio and energy consumption. The first optimization strategy is conducted in four steps under distillation purity specifications: Aspen Plus or Prosim Plus simulator built-in SQP method is used for the optimization of the continuous variables: R1, R2 and FE by minimizing OF in open loop flowsheet (step 1). Then, a sensitivity analysis is performed to find optimal values of D1, D2 (step 2) and NFE, NFAB, NFReg (step 3), while step 1 is done for each set of discrete variables. Finally the design is simulated in closed loop flowsheet, and we calculate TAC and Eext and eext (step 4). We also derive from mass balance the non-linear relationships between the two distillates and how they relate product purities and recoveries. The results show that double digit savings can be achieved over designs published in the literature thanks to the improving of Eext and eext. Then, we study the influence of the Eext and eext on the optimal solution, and we run the second multiobjective optimization strategy. The genetic algorithm is usually not sensitive to initialization. It allows finding optimal total tray numbers N1, N2 values and is directly used with the closed loop flow sheet. Within Pareto front, the effects of main variables FE/F and R1 on TAC and Eext are shown. There is a maximum Eext (resp. minimum R1) for a given R1 (resp. Eext). There exists an optimal efficiency indicator Eext,opt which corresponds to the optimal design with the lowest TAC. Eext,opt can be used as a complementary criterion for the evaluation of different designs. Through the analysis of extractive profile map, we explain why Eext increases following the decrease of FE and the increase of R1 and we relate them to the tray numbers. With the sake of further savings of TAC and increase of the environmental performance, double-effect heat integration (TEHI) and mechanical heat pump (MHP) techniques are studied. In TEHI, we propose a novel optimal partial HI process aiming at the most energy saving. In MHP, we propose the partial VRC and partial BF heat pump processes for which the coefficients of performance increase by 60% and 40%. Overall, optimal partial HI process is preferred from the economical view while full VRC is the choice from the environmental perspective.

Les avantages que présentent les systèmes électriques par rapport aux autres systèmes (mécaniques, hydrauliques et pneumatiques) ont permis d’intensifier l’électrification des systèmes embarqués à bord des aéronefs : c’est le concept d’avion plus électrique. Dans ce contexte, l’approche de conception intégrée par optimisation (CIO) de ces systèmes s’avère aujourd’hui une nécessité pour pouvoir répondre aux exigences en termes d’efficacité énergique, de fiabilité et de masse... Dans cette thèse, nous avons appliqué la CIO à une chaine de conversion électromécanique utilisée dans le système de conditionnement d’air d’un avion. Deux objectifs sont ciblés : la minimisation de la masse du système et l’augmentation de son efficacité énergétique. Ces objectifs sont intégrés à diverses contraintes hétérogènes, allant de la qualité réseau au respect de la mission de vol dans le plan couple – vitesse, en passant par la thermique,… Compte tenu de la complexité du système étudié et de son caractère multidisciplinaire, des approches de conception par optimisation dites « MDO » (pour Multidisciplinary Design Optimization) sont étudiées. En effet, au delà des compétences physiques et techniques, la conception intégrée par optimisation des systèmes complexes nécessite des efforts supplémentaires en termes de méthodologies de conception. Nous avons présenté dans cette thèse trois approches : Approches mono-niveau : séquentielle et globale ; Approche multi-niveaux, couplant niveaux système et niveau constituants (filtre, onduleur, machine) ; des formulations adaptées à notre problème de conception sont présentées afin de résoudre les problèmes liés aux optimisations mono-niveau. Les performances des différentes approches de conception sont présentées analysées et comparées. Les résultats obtenus montrent clairement les avantages que présente la formulation multi-niveaux par rapport aux approches classiques de conception. / The benefits of electrical systems compared to other systems (mechanical, hydraulic and pneumatic) are a serious motivation for the electrification of embedded systems in “more electric aircraft”. In this framework, the integrated optimal design of these systems appears necessary to meet requirements in terms of efficiency, reliability and weight reduction. In this thesis, we have applied the integrated optimal design to an electromechanical system used in the air conditioning system of a more electric aircraft. Two objectives are targeted: the minimization of the system weight and the increase of its efficiency. Both objectives are integrated with several heterogeneous constraints, from network quality till flight mission fulfilment in the torque vs speed plan. Because of the complexity of the studied system and its multidisciplinary nature, "MDO" approaches (for multidisciplinary Design Optimization) are studied. In fact, beyond physical and technical skills, integrated optimal design of complex systems requires additional efforts in terms of design methodologies. Three approaches are presented in this thesis: One-level Approaches: sequential and global; Multilevel approach, coupling “system” level with “device” level (filter, inverter, electric machine); a set of formulations adapted to our design problem are presented to solve the issues associated to the one-level approaches. The performance of these design approaches are presented, analyzed and compared. The results clearly show the advantages that involves multilevel formulation compared to conventional design approaches.

Um tema pouco estudado na literatura, mas frequentemente encontrado por empresas prestadoras de serviço, é o Problema de Escalonamento de Técnicos de Campos (Field Technician Scheduling Problem). O problema consiste em associar um número de tarefas - em diversos locais, com diferentes prioridades e com janelas de tempo - a uma quantidade de técnicos - com diferentes horários de expediente e com habilidades distintas - que saem no início do horário de trabalho da sede da empresa, para onde devem retornar antes do fim do expediente. Cada tarefa é atendida por um único técnico. Esse problema é estudado neste trabalho. A primeira parte do trabalho apresenta um modelo de programação linear inteira mista (PLIM) e, dada a complexidade do problema, heurísticas construtivas e meta-heurísticas foram desenvolvidas. Na função objetivo, procura-se principalmente maximizar o número ponderado de tarefas executadas em um dia de trabalho, de acordo com as suas prioridades. Em linhas gerais, as heurísticas construtivas ordenam as tarefas de acordo com um critério pré-estabelecido e, em seguida, designam cada uma a um dos técnicos capazes de realiza-la sem violar as restrições do problema. Tendo em conta o bom desempenho obtido em outros problemas semelhantes, foi adotado um Algoritmo Genético denominado Biased Random-Key Genetic Algorithms (BRKGA), que utiliza chaves aleatórias para codificar e decodificar as soluções. Codificadores e decodificadores adaptados ao problema foram desenvolvidos e testes computacionais são apresentados. As soluções obtidas em problemas de pequenas dimensões são comparadas com as soluções ótimas conhecidas e, para aprimorar a avaliação do desempenho nas instâncias médias e grandes, quatro procedimentos para obter limitantes superiores foram propostos. Testes computacionais foram realizados em 1040 instâncias. O BRKGA encontrou 99% das 238 soluções ótimas conhecidas e, nas 720 instâncias de dimensões médias e grandes, ficou em média a 3,8% dos limitantes superiores. As heurísticas construtivas superaram uma heurística construtiva da literatura em 90% das instâncias. A segunda parte do trabalho apresenta uma nova abordagem para o Problema de Escalonamento de Técnicos de Campo: um modelo biobjetivo, onde uma segunda função objetivo buscará que as tarefas prioritárias sejam realizadas o mais cedo possível. Uma versão multiobjectivo do BRKGA foi desenvolvida, considerando diversas estratégias para classificar a população do algoritmo e escolher as melhores soluções (estratégias de elitismo). Codificadores e decodificadores foram criados para o problema multiobjectivo. Os resultados computacionais obtidos são comparados com os resultados de um Algoritmo Genético conhecido na literatura, o Nondominated Sorting Genetic Algorithm II (NSGA II). Para instâncias de pequenas dimensões, os resultados da meta-heurística proposta também são comparados com a fronteira ótima de Pareto de 234 instâncias, obtidas por enumeração completa. Em média, o BRKGA multiobjectivo encontrou 94% das soluções da fronteira ótima de Pareto e, nas instâncias médias e grandes, superou o desempenho do NSGA-II nas medidas de avaliação adotadas (porcentagem de soluções eficientes, hipervolume, indicador epsílon e cobertura). / An important topic in service companies, but little studied until now, is the field technician scheduling problem. In this problem, technicians have to execute a set of jobs or service tasks. Technicians have different skills and working hours. Tasks are in different locations within a city, with different time windows, priorities, and processing times. Each task is executed by only one technician. This problem is addressed in this thesis. The first part of the research presents the mixed integer linear programming model (MILP) and, due to the complexity of this problem, constructive heuristics and metaheuristics were proposed. The objective function is to maximize the sum of the weighted performed tasks in a day, based on the priority of tasks. In general terms, in the proposed constructive heuristics, jobs are ordered according to a criterion and, after that, tasks are assigned to technicians without violating constraints. A Genetic Algorithm (the Biases Randon Key Genetic Algorithm - -RKGA) is applied to the problem, based on its success in similar problems; the BRKGA uses random keys and a decoder transforms each chromosome of the Genetic Algorithm into a feasible solution of the problem. Decoders and encoders adapted to the problem were developed and computational tests are presented. A comparison between the solutions of the heuristic methods and optimal solutions values was also conducted for small instances and, to analyze medium and large instances, four upper bound models were proposed. Computational experiments with 1040 instances were carried out. The BRKGA reached 99% of the 238 optimal solutions and, for 720 medium and large instances, the average upper bound gap was 3,8%. Constructive heuristics overcame a heuristic of the literature in 90% of the instances. The second part of this research presents a new approach of the Field Technician Scheduling Problem: a multiobjective model, with a second objective function to execute the priority tasks as soon as possible. A multiobjective BRKGA was developed, with different strategies to classify the Genetic Algorithm population and to select the elite solutions (elite strategies). Decoders and encoders were developed for the multiobjective problem too. The results were compared with a known Genetic Algorithm, the Nondominated Sorting Genetic Algorithm II (NSGA II). For 234 small instances, the results were compared with the Pareto optimal solutions, obtained by complete enumeration. On average, the BRKGA found 94% of the Pareto optimal solutions and, for 720 medium and large instances, outperformed the NSGA-II by means of the measures adopted (percentage of efficient solutions, hypervolume, epsilon and coverage).

Submitted by Ronildo Prado (ronisp@ufscar.br) on 2016-09-23T20:10:21Z No. of bitstreams: 1 DissEP.pdf: 2850814 bytes, checksum: 13c476dc7f26d54826c6932c0fa4fcd2 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2016-09-23T20:10:38Z (GMT) No. of bitstreams: 1 DissEP.pdf: 2850814 bytes, checksum: 13c476dc7f26d54826c6932c0fa4fcd2 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2016-09-23T20:10:49Z (GMT) No. of bitstreams: 1 DissEP.pdf: 2850814 bytes, checksum: 13c476dc7f26d54826c6932c0fa4fcd2 (MD5) / Made available in DSpace on 2016-09-23T20:10:57Z (GMT). No. of bitstreams: 1 DissEP.pdf: 2850814 bytes, checksum: 13c476dc7f26d54826c6932c0fa4fcd2 (MD5) Previous issue date: 2015-03-31 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Currently there is a growing increase in fuel consumption, but also an increased concern about the end of fossil fuels and their environmental damage. In this scenario, secondgeneration ethanol (E2G), produced from sugarcane bagasse, appears as an option to increase the production of first generation ethanol (E1G), produced from sugarcane. The aim of this study was to evaluate the production of ethanol, the generation of electricity, CO2 emissions and vinasse into an E1G and E2G autonomous distillery through multiobjective optimization. This assessment has been formulated in terms of multi-objective optimization problems in virtual biorefinery modeled in EMSO (Environment for Modeling, Simulation and Optimization). The modeling of closed water circuits, CO2 production in the boiler and in the fermenter, and the process of concentrating the juice and vinasse streams through multiple-effect evaporators, and the multiobjective optimization involving the production of E2G, electric energy and production of CO2 and vinasse were performed. The modeled biorefinery processes 500,000 kg/h of sugarcane and burns, in addition to bagasse, 35,000 kg/h of sugarcane straw. The multiple effect evaporators for the broth concentration generated savings of around 18% in turbine backpressure exhaust steam when compared to a process with a single effect. The concentration of the vinasse through multiple-effect evaporators can cause a reduction in flow rate of more than 70%. The obtained non-dominated solutions in multiobjective optimization studies have shown a relationship among the production of ethanol, vinasse, energy and CO2 as a function of the decision variables: bagasse fraction diverted to produce E2G, and fraction of vinasse concentrated in multiple effect evaporators. Nondominated solutions are in the bagasse fraction range from 0.01% to 50.09%, and vinasse fraction comprises values greater than 14.09%. Among the solutions, ethanol flow was between 35,730 kg/h and 41,633 kg/h. CO2 production can reach values above 187,000 kg/h considering the CO2 released in the fermenters and in the boiler. On the issue of electricity generation, values above 83,000 kW can be reached. The results showed that the methodology used was efficient and the proposed objectives have been met. / Com o crescente aumento do consumo de combustíveis e o aumento da preocupação com o fim dos combustíveis fósseis e com seus danos ambientais, o etanol de segunda geração (E2G), produzido a partir do bagaço e da palha da cana-de-açúcar, surge como uma opção para aumentar a produção de etanol de primeira geração (E1G), produzido a partir da cana-de-açúcar. O objetivo desse trabalho foi avaliar a produção de etanol, a geração de energia elétrica, a emissão de CO2 e de vinhaça em uma destilaria autônoma de E1G e E2G empregando a otimização multiobjetivo. Essa avaliação foi formulada em termos de problemas de otimização multiobjetivo na biorrefinaria virtual modelada em EMSO (Environment for Modeling, Simulation and Optimization). A modelagem de circuitos fechados de água, da produção de CO2 na caldeira e no fermentador, e do processo de concentração das correntes de caldo e de vinhaça por meio de evaporadores múltiplo efeito, bem como a otimização multiobjetivo envolvendo a produção de E1G e E2G, geração de energia e produção de vinhaça, foram realizados. A biorrefinaria modelada processa 500.000 kg/h de cana-de-açúcar e queima, além de bagaço, 35.000 kg/h de palha de cana-de-açúcar. Com os evaporadores múltiplo efeito para a concentração do caldo, foi possível uma economia na ordem de 18% no vapor de escape da turbina de contrapressão em comparação a um processo de simples efeito. A concentração da vinhaça, por meio de evaporadores múltiplo efeito, pode provocar uma redução da vazão de mais de 70%. As soluções não-dominadas obtidas nos estudos de otimização multiobjetivo mostraram uma relação entre a produção de etanol, de vinhaça, de energia e de CO2 em função das variáveis de decisão: fração de bagaço destinado para a produção de E2G, e fração de vinhaça destinada para a concentração nos evaporadores de múltiplo efeito. As soluções não-dominadas se encontram no intervalo de fração de bagaço entre 0,01% e 50,09%, enquanto a fração de vinhaça compreende valores acima de 14,09%. Entre as soluções, a vazão de etanol ficou entre 35.730 kg/h e 41.633 kg/h. A produção de CO2 pode chegar a valores acima dos 187.000 kg/h, considerando o CO2 liberado nos fermentadores e na caldeira. No quesito geração de energia elétrica, consegue-se chegar a valores acima de 83.000 kW. Os resultados mostraram que a metodologia utilizada foi eficiente e os objetivos propostos foram atendidos.

Orientador: Paulo Morelato França / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-05T20:11:19Z (GMT). No. of bitstreams: 1 Garcia_ViniciusJacques_D.pdf: 1756755 bytes, checksum: e845cc09a5de807da958e9792684e777 (MD5) Previous issue date: 2005 / Resumo: Depois da regulamentação do setor elétrico brasileiro, a qualidade no fornecimento de energia ganhou maior importância por parte das concessionárias. Neste contexto, o problema de restauração do serviço tem particular relevância pela relação com a freqüência e duração das interrupções no fornecimento: através de alterações na configuração original da rede, busca-se reduzir a carga não atendida sem deixar de observar as restrições de capacidade dos alimentadores, de queda de tensão nas barras de carga e de radialidade da rede. Considerando o caráter temporário destas manobras, torna-se desejável reduzir o grau de intervenção de modo a facilitar a restauração da configuração original. Nesta tese é considerado o problema multiobjetivo de restauração do serviço que compreende a minimização da carga sem fornecimento e do número de chaves manipuladas. Depois da definição matemática do problema, da revisão da literatura especializada e da descrição de um "framework" para problemas relacionados, são descritas duas heurísticas, uma construtiva e outra de melhoramento. A seguir, apresentam-se duas metaheurísticas para o problema, uma Busca Tabu e um Algoritmo Evolutivo, ambas baseadas em otimização de Pareto. Por fim, por meio de estudos práticos com sistemas de distribuição brasileiros, avalia-se experimentalmente a aplicabilidade das abordagens propostas / Abstract: After the Brazilian electric power market regulation, quality of service became a crucial concern of utilities. In fact, the service restoration has a particular importance since it is closely related to frequency and duration of service interruption: through network reconfigurations, one aims to reduce the non supplied load while respecting constraints like feeder and voltage limits as well as the maintenance of a radial structure. Considering that this emergency state is transitory existing only until the fault is eliminated, it is convenient to reduce the number of switching operations in order to make the return back to the original configuration easy. This work considers the multiobjective service restoration to minimize both the load not supplied and the number of switching operations. After defining the mathematical formulation proposed and presenting the bibliographical survey with the description of a new framework to related problems, two new heuristics are presented, one for constructive search and another one for neighborhood search. Next, two metaheuristics especially developed for the referred problem are described, both based on Pareto optimization. Finally, the effectiveness of these proposed methods are proved in a set of five systems, three of them referring to actual Brazilian systems / Doutorado / Automação / Doutor em Engenharia Elétrica

Made available in DSpace on 2014-07-29T15:01:46Z (GMT). No. of bitstreams: 1 Dissertacao_Maira de Carvalho.pdf: 846890 bytes, checksum: 1b876a63defdf3d8fc33aa92bba455c5 (MD5) Previous issue date: 2011-08-29 / CARVALHO, M. Calibration models of urban drainage using multiobjective evolutionary algorithms. 2011. Dissertation (Masters of Environmental Engineering) - Civil Engineering College, Post-Graduation Stricto Sensu Program in Environmental Engineering - Federal University of Goiás, Goiânia, Goiás, Brazil, 2011.. This study proposed to develop and implement a calibration routine hydrological models applied to urban drainage using multiobjective optimization techniques. To make this work possible model was adopted Storm Water Management Model (SWMM) and the computational algorithms developed in MATLAB environment using an evolutionary algorithm. The method was applied to two different levels of detail in representing the Arroyo Cancels basin, located in the urban area of Santa Maria-RS, submitted to the hydrological processes involved in the process of rainfall-runoff transformation in the search for optimal values of hydrological parameters the basin. Objective functions were defined and applied simultaneously in the calibration parameters. Worked with the simulation of events of low and high intensity settings for two discretization of the watershed, and other simple and subdivided into 18 sub-basins. The sensitivity analysis performed made it possible to check that the parameters that most influenced the basin were simple: Percentage of impervious area and outlet width. Regarding the results for the various watershed discretization can be seen that in most cases when working with a more detailed watershed they were better, except for some isolated events. Overall the model showed better results when high-intensity simulated events for the best compromise solutions, thus showing the importance of using a multiobjective model. / CARVALHO, M. Calibração de modelos de drenagem urbana utilizando algoritmos evolucionários multiobjetivo. 2011. Dissertação (Mestrado em Engenharia do Meio Ambiente) Escola de Engenharia Civil, Programa de Pós-Graduação Stricto Sensu em Engenharia do Meio Ambiente, Universidade Federal de Goiás, Goiânia, 2011. O presente trabalho propôs desenvolver e aplicar uma rotina de calibração de modelos hidrológicos aplicados a drenagem urbana empregando técnicas de otimização multiobjetivo. Para tornar possível a realização deste trabalho foi adotado o modelo Storm Water Management Model (SWMM) e as rotinas computacionais desenvolvidas em ambiente MATLAB, utilizando um algoritmo evolucionário. O método foi aplicado a dois diferentes níveis de detalhamento na representação da bacia do Arroio Cancela, localizada na zona urbana do município de Santa Maria-RS, na busca de valores ótimos de parâmetros hidrológicos da bacia. Foram definidas funções objetivo e aplicadas simultaneamente na calibração de parâmetros. Trabalhou-se com a simulação de eventos de baixa e alta intensidade para duas configurações de bacia hidrográfica, sendo simples e outra subdividida em 18 sub-bacias. A análise de sensibilidade realizada possibilitou a verificação de que os parâmetros que mais influenciaram na bacia simples foram: Porcentagem de área impermeável e Largura do escoamento. Em relação aos resultados para as diferentes configurações de discretização da bacia hidrográfica pode-se verificar que na maioria dos casos quando se trabalhou com uma bacia mais detalhada estes foram melhores, salvo alguns eventos isolados. No geral o modelo apresentou melhores resultados quando simulou eventos de alta intensidade para as soluções de melhor compromisso, assim mostrando a importância da utilização de um modelo multiobjetivo.