Um calibrador automático multiobjetivo para o Storm Water Management Model (SWMM) foi desenvolvido utilizando o método de otimização multiobjetivo Non Dominated Sorting Genetic Algorithm (NSGA II) com elistismo controlado (Deb & Goel, 2001). O programa utiliza o código fonte do SWMM na etapa de avaliação das soluções, para determinar o valor das vazões simuladas, utilizado no cálculo das funções objetivo (FOs). Os testes do calibrador foram aplicados a dois sistemas diferentes, sendo o primeiro uma bacia exemplo hipotética disponibilizada no pacote de instalação do SWMM e o segundo a bacia do córrego do Gregório, localizada no município de São Carlos (SP). Foi realizada a análise de sensibilidade para os dois sistemas, visando determinar os parâmetros a serem calibrados. De modo geral, a porcentagem de áreas impermeáveis e os parâmetros de rugosidade e de infiltração apresentaram maior influência sobre a resposta do sistema em termos de vazão de pico e volume total escoado das bacias. O programa desenvolvido se mostrou eficiente para ambos os sistemas calibrados, com coeficientes de eficiência de Nash & Sutcliffe (1970) médios de 0,99 para a bacia exemplo e 0,87 para a bacia do córrego do Gregório, respectivamente, com um número reduzido de iterações. Construído o calibrador, testes foram realizados para identificar a melhor combinação de FOs e a abordagem multievento mais eficiente. Para tanto, foram testadas 55 diferentes combinações de FOs duas a duas. Os resultados evidenciaram que a melhor combinação testada foi a F2-F6, e a abordagem multievento mais eficiente foi a avaliação da médias das FOs, considerando todos os eventos utilizados na etapa de calibração. Cabe ressaltar que estas conclusões se aplicam somente ao sistema considerado neste estudo. Por fim, a validação comprovou a eficiência do calibrador, aplicada a 10 eventos distintos registrados na bacia do córrego do Gregório, com coeficiente de eficiência médio de 0,84. / An automatic multiobjective calibrator for the Storm Water Management Model (SWMM) was developed using the Non Dominated Sorting Genetic Algorithm (NSGA II) method with controlled elitism (Deb & Goel, 2001). The software uses the SWMM source code for evaluating the solutions, to determine the simulated flow values, used in the objective functions (OFs) calculation. The calibrator tests were applied on two different systems, a hypothetical example basin provided jointly to the SWMM installation package, and the basin of Gregório stream, located in São Carlos (SP). The sensitivity analysis was performed for both systems to determine the parameters to be calibrated. Generally, the percent of imperviousness, the roughness and infiltration parameters variations resulted in large modifications on the system response in terms of peak flow and total runoff volume. The developed software proved to be efficient for both calibrated systems, presenting an average of the Nash & Sutcliffe (1970) efficiency coeficient of 0.99 and 0.87 for the example basin and the Gregório stream basin, respectively, with a few number of iterations. After the calibrator built, tests were conducted aiming to identify the best OFs combination and the more efficient multievent approach. Thus, 55 different combinations in pairs of OFs were tested. The results showed that the best combination tested was the F2-F6 and most efficient multievent approach was the evaluation of the OFs means, considering all the calibration events. It is worth noting that these conclusions apply only to the system considered in this study. Finally, the validation confirmed the calibrator efficiency, applied to 10 different events recorded in the Gregório stream basin, presenting an average of the efficiency coeficient of 0.84.

Um calibrador automático multiobjetivo para o Storm Water Management Model (SWMM) foi desenvolvido utilizando o método de otimização multiobjetivo Non Dominated Sorting Genetic Algorithm (NSGA II) com elistismo controlado (Deb & Goel, 2001). O programa utiliza o código fonte do SWMM na etapa de avaliação das soluções, para determinar o valor das vazões simuladas, utilizado no cálculo das funções objetivo (FOs). Os testes do calibrador foram aplicados a dois sistemas diferentes, sendo o primeiro uma bacia exemplo hipotética disponibilizada no pacote de instalação do SWMM e o segundo a bacia do córrego do Gregório, localizada no município de São Carlos (SP). Foi realizada a análise de sensibilidade para os dois sistemas, visando determinar os parâmetros a serem calibrados. De modo geral, a porcentagem de áreas impermeáveis e os parâmetros de rugosidade e de infiltração apresentaram maior influência sobre a resposta do sistema em termos de vazão de pico e volume total escoado das bacias. O programa desenvolvido se mostrou eficiente para ambos os sistemas calibrados, com coeficientes de eficiência de Nash & Sutcliffe (1970) médios de 0,99 para a bacia exemplo e 0,87 para a bacia do córrego do Gregório, respectivamente, com um número reduzido de iterações. Construído o calibrador, testes foram realizados para identificar a melhor combinação de FOs e a abordagem multievento mais eficiente. Para tanto, foram testadas 55 diferentes combinações de FOs duas a duas. Os resultados evidenciaram que a melhor combinação testada foi a F2-F6, e a abordagem multievento mais eficiente foi a avaliação da médias das FOs, considerando todos os eventos utilizados na etapa de calibração. Cabe ressaltar que estas conclusões se aplicam somente ao sistema considerado neste estudo. Por fim, a validação comprovou a eficiência do calibrador, aplicada a 10 eventos distintos registrados na bacia do córrego do Gregório, com coeficiente de eficiência médio de 0,84. / An automatic multiobjective calibrator for the Storm Water Management Model (SWMM) was developed using the Non Dominated Sorting Genetic Algorithm (NSGA II) method with controlled elitism (Deb & Goel, 2001). The software uses the SWMM source code for evaluating the solutions, to determine the simulated flow values, used in the objective functions (OFs) calculation. The calibrator tests were applied on two different systems, a hypothetical example basin provided jointly to the SWMM installation package, and the basin of Gregório stream, located in São Carlos (SP). The sensitivity analysis was performed for both systems to determine the parameters to be calibrated. Generally, the percent of imperviousness, the roughness and infiltration parameters variations resulted in large modifications on the system response in terms of peak flow and total runoff volume. The developed software proved to be efficient for both calibrated systems, presenting an average of the Nash & Sutcliffe (1970) efficiency coeficient of 0.99 and 0.87 for the example basin and the Gregório stream basin, respectively, with a few number of iterations. After the calibrator built, tests were conducted aiming to identify the best OFs combination and the more efficient multievent approach. Thus, 55 different combinations in pairs of OFs were tested. The results showed that the best combination tested was the F2-F6 and most efficient multievent approach was the evaluation of the OFs means, considering all the calibration events. It is worth noting that these conclusions apply only to the system considered in this study. Finally, the validation confirmed the calibrator efficiency, applied to 10 different events recorded in the Gregório stream basin, presenting an average of the efficiency coeficient of 0.84.

The job scheduling problem is a type of scheduling problem where a list of jobs and machines are given. A solution consists of a schedule where each job is assigned to one or multiple machines at a certain time. In this study, a multiobjective evolutionary algorithm called NSGA-II was applied to optimize schedules for a particular scheduling problem given by a board game made by the Swedish educative company INSU. The scheduling problem features novel restrictions on the schedules, such as transportation delay between the jobs, skill requirements for the machines to fulfill. The board game also allows pre-emption, i.e., that the jobs can be paused and resumed by the same or other machines. These restrictions impose a challenge for creating a genetic representation for the evolutionary algorithm and a decoder which decodes the representation into a schedule. This problem was solved by proposing a new genetic representation based on previous work and testing it with a few crossover and mutation methods in two experiments. The experiments found that the new representation is effective in creating high-quality schedules, but it is inconclusive as to which crossover and mutation method is the most effective. The decoder’s execution time was also measured, which showed that the decoder scales rapidly with an increasing number of jobs. Despite this, the new representation and decoder are useful for optimizing other scheduling problems with pre-emption and other restrictions.

Dans ce mémoire, nous nous intéressons à l’optimisation des mouvements improductifs de chargement/déchargement, appelés shiftings, dans les problèmes de transport. Dans le premier contexte,nous introduisons le problème de shifting dans le cas du voyageur de commerce. Notre objectif est de chercher un circuit hamiltonien qui optimise à la fois le coût distance et le coût shifting. Nous proposons une modélisation mathématique du problème, puis, nous adaptons la métaheuristique d’optimisation par colonies de fourmis sous sa forme séquentielle et parallèle pour le résoudre. Dans le deuxième contexte, nous abordons le problème d’optimisation des plans de chargement et d’arrimage des conteneurs dans des barges. Ce problème consiste à chercher l’emplacement le plus convenable de chaque conteneur dans les barges de façon à faciliter son déchargement dans la chronologie des ports à visiter. D'abord, nous introduisons une modélisation mathématique du problème dans le cas d’une seule barge ou différents ports du trajet ont des coûts shiftings non-uniformes. L’objectif est d’optimiser le coût total de shiftings, la stabilitélongitudinale de la barge et celle transversale. Ensuite, nous généralisons le problème au cas d’un système de convoi de barges. Nous proposons, d’abord, un modèle mathématique en nombres entiers, dans lequel, nous considérons l’aspect multi-objectif en optimisant le nombre de shiftings, la stabilité du convoi et le nombre de barges utilisées dans le convoi. Puis, nous adaptons la méthode nsga-II en se basant sur les heuristiques du problème de bin-packing.L'ensemble des résultats obtenus est évalué en utilisant des mesures de performances adaptées au problème. / This work outlines the optimization of unproductive loading/unloading movements, called shiftings, in transport problems. in the first context, we introduce the shifting in the case of the traveling salesman problem. our goal is to find a hamiltonian circuit that optimizes both distance and shifting costs. we propose a mathematical modeling of the problem, and then we adapt the ant colony optimization metaheuristic in its sequential and parallel form to solve it. in the second context, we address the 3d container stowage planning problem of barges. this problem consists in finding the most suitable location of each container in the barge in order to facilitate its retrieval in the chronology of ports to be visited. firstly, we introduce a mathematical modeling of the problem in the case of a single barge where different ports are of non-uniform operational costs. the main objective is to optimize the total shiftings fees, the longitudinal stability of the barge and the transverse one. then, we generalize our problem to the case of barge convoy systems. we first propose a suitable mathematical modeling, in which, we consider the multi-objective aspect by optimizing the total number of shiftings, the convoy stability and the number of the real-used barges in the convoy. in order to solve this new variant, we propose a novel adaptation of the multi-objective evolutionary algorithm nsga-ii (non-dominated sorting genetic algorithm-ii) based on a set of heuristics introduced by the bin-packing problem resolution methods. the numerical results are evaluated using performance measures adapted to theproblem.

Made available in DSpace on 2017-07-10T17:11:49Z (GMT). No. of bitstreams: 1 Ana Paula P T Caetano 2.pdf: 4372875 bytes, checksum: b5eda892daea23dd9f2cf33a7a4045c5 (MD5) Previous issue date: 2015-03-20 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The simulation results obtained using three models which minimize the distribution system reliability indexes and investment through sectionalizing switches allocation and/ or installation of tie lines are presented in this work. This is a problem with conflicting goals that were simultaneously minimized through a multi-objective Genetic Algorithm (Non- Dominated Sorting Genetic Algorithm II - NSGA II), seeking trade-off solutions between investment costs and network reliability. As constraints, the continuity indexes (DEC and FEC) and the power flow of the system were considered. The three models presented have two objective functions, being the first one the investment cost (CINV) of allocated equipment. The second function is one of three reliability indexes: Cost of Energy not Supplied (CENS), DEC and FEC. In the first model (CINV and CENS), results with higher quantities of sectionalizing switches allocation were found, so it was the model which presented higher investment costs. In the second model (CINV and DEC) results presenting lower values for the DEC were found, comparing with the first model, and lower investment cost, but the total cost were similar to those of the first model, since it has an increased CENS. The third model (CINV and FEC) was the model which allocated less sectionalizing switches and presented lower investment costs, since the allocation of these devices do not influence the minimization of FEC, only the allocation of tie lines change the system configuration influencing the FEC. All results obtained through the models met the expectations of finding a set of diverse solution considering the constraints. / Neste trabalho foram apresentados e analisados os resultados obtidos de três modelos matemáticos que minimizam indicadores de confiabilidade do sistema de distribuição e custo de investimento através da alocação de chaves seccionadoras e/ou instalação de ramais de interconexão. Trata-se de um problema com objetivos conflitantes que foram minimizados simultaneamente através de um algoritmo genético multiobjetivo (Non-Dominated Sorting Genetic Algorithm II NSGA II), buscando soluções com bons compromissos (trade-off) entre o custo de investimento e a confiabilidade da rede. Foram considerados como restrições os indicadores de continuidade (DEC e FEC) e o fluxo de potência do sistema. Os três modelos apresentados possuem duas funções objetivos, uma das funções representa o custo de investimento (CINV) dos equipamentos alocados e a outra função é um indicador de confiabilidade, sendo que foram adotados o custo de energia não suprida (CENS) e os indicadores DEC e FEC respectivamente ao primeiro, segundo e terceiro modelo. No primeiro modelo (CENS e CINV) foram encontrados resultados com maior quantidade de alocação de chaves, deste modo foi o modelo que apresentou maiores custos de investimentos. No segundo modelo (DEC e CINV) foram encontrados resultados com menores valores para o DEC em relação ao primeiro modelo e com menor custo de investimento, porém com custo total aproximados dos valores do primeiro modelo, visto que tiveram um aumento do CENS. O terceiro modelo (FEC e CINV) foi o modelo que menos alocou chaves seccionadoras e apresentou menores custos de investimento, uma vez que a alocação destes dispositivos não influencia na minimização do FEC, somente a alocação dos ramais de interconexão que alteram a configuração do sistema influenciando no FEC. Todos os resultados obtidos nos modelos atenderam às expectativas de encontrar um conjunto de solução diversificado respeitando as restrições impostas.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2018-01-10T09:42:22Z No. of bitstreams: 2 Dissertação - Hélios Kárum de Oliveira Bastos - 2017.pdf: 2219804 bytes, checksum: ba853c18f7e7e2c65eb0a342d4a34640 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-01-10T09:42:46Z (GMT) No. of bitstreams: 2 Dissertação - Hélios Kárum de Oliveira Bastos - 2017.pdf: 2219804 bytes, checksum: ba853c18f7e7e2c65eb0a342d4a34640 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-01-10T09:42:46Z (GMT). No. of bitstreams: 2 Dissertação - Hélios Kárum de Oliveira Bastos - 2017.pdf: 2219804 bytes, checksum: ba853c18f7e7e2c65eb0a342d4a34640 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-08-24 / Multiobjective Optimization for feature and samples selection in double chromosome of integer representation and variable size for multivariate calibration} In several problems of regression, classification, prediction, approximation Optimization, the original data contain a large number of variables to obtain a better representation of the problem under consideration. However, a significant part of the variables may be irrelevant and redundant from the point of view of machine learning. Indeed, one of the challenges to be overcome is a selection of a subset of variables that has the best perform. One of the breakthroughs in this type of problem is the use of a multiobjective formulation that avoids the overlap of the model to the training data set. Another important point is the process of choosing the objects to be used in the learning stage. Generally, a selection of variables and treatment objects are treated separately and without dependence. This project proposes a multiobjective modeling to select variables and objects simultaneously using a genetic integer representation algorithm with variable size chromosomes. It is expected that a simultaneous selection of objects and variables on a multiobjective context produce better results in a traditional approach. As a case study this work utilized an analysis of near infrared (NIR) material on oil samples for the purpose of estimating the concentration of an interest properties such set was used in the competition conducted at the International Diffuse Reflectance Conference (IDRC) in the year 2014. / Em diversos problemas de regressão, classificação, previsão, aproximação e otimização, os dados originais contêm um grande número de variáveis introduzidas para se obter uma melhor representação do problema considerado. Entretanto, uma parte significativa destas variáveis podem ser irrelevantes e/ou redundantes do ponto de vista do aprendizado de máquina acerca do problema. Com efeito, um dos desafios a ser superados é a seleção de um subconjunto de variáveis que apresentem um melhor desempenho. Um dos avanços recentes neste tipo de problema está no uso de uma formulação multiobjetivo que evita o superajuste do modelo ao conjunto de dados de treinamento. Outro ponto importante refere-se ao processo de escolha adequada dos objetos a serem utilizados na etapa de aprendizado. Geralmente, a seleção de variáveis e de objetos de treinamento são tratados de forma separada e sem dependência. Este projeto propõe uma modelagem multiobjetivo para seleção de variáveis e objetos de forma simultânea utilizando-se de algoritmo genético de representação inteira com cromossomos de tamanho variáveis. Espera-se que a seleção simultânea de objetos e variáveis no contexto multiobjetivo produza melhores resultados em relação a abordagem tradicional. Como estudo de caso este trabalho utiliza dados obtidos por uma análise de material com ondas de infravermelho próximo (NIR) sobre amostras de petróleo com o propósito de estimar a concentração de uma propriedade de interesse, tal conjunto foi utilizado na competição realizada no International Diffuse Reflectance Conference (IDRC) (\url{http://cnirs.clubexpress.com/content.aspx?page_id=22&club_id=409746&module_id=19 0211}), no ano de 2015.

An aerodynamic shape optimization procedure was performed on a low observable engineintake duct. The intake duct was fixed in its throat and aerodynamic interface plane (AIP)sections, while leaving up to 7 design parameters free to deformation in the centroid curveand mid section profile. The optimization setup consisted of an optimizer block implementedin MATLAB, where the NSGA-II optimization algorithm was implemented, and a simulationblock using computational fluid dynamics (CFD). The objective functions for the optimizationprocess were the pressure recovery and the DC60 distortion coefficient in the AIP section.In total, four optimizations with gradually increasing degrees of deformation were conducted.The first optimization process was a validation case, performed on a test duct design, whilethe remaining optimizations were performed using a duct designed by the Swedish DefenceResearch Agency (FOI) as a starting point, for cruise and take-off conditions. The connection of NSGA-II and the CFD setup proved useful, as the distortion was decreasedby up to 52.8% relative the original value while keeping the pressure recovery within 0.06% ofthe original duct. The algorithm was successful in finding an improvement for both consideredoperating conditions, with the largest improvement for the cruise case. In total 975 duct designswere evaluated in the four processes, using a uniform inflow boundary condition on a boundaryextruded one meter from the throat of the intake duct. The importance of the handling of non-converged solutions in the automated optimizationprocess was also pointed out, as an oscillating solution affected the third optimization, therebyrendering that solution useless. / En aerodynamisk formoptimering av en insynsskyddad luftintagskanal för en stridsdrönaregenomfördes genom att koppla den genetiska optimeringsalgoritmen NSGA-II samt CFD i enautomatiserad process. Optimeringens två målfunktioner var att maximera tryckåtervinstenoch minimera flödesdistorsionen på AIP-randen. Luftintagskanalen som användes som basför optimeringen var fixerad vid inlopps- samt AIP-profilerna, medan deformation tilläts imellanliggande delar, styrt av upp till 7 styrparametrar. Den kanal som användes som bas föroptimeringsprocessen togs fram av FOI, Totalförsvarets Forskningsinstitut, i samband med ettNATO-STO projekt för den obemannade stirdsdrönaren MULDICON. Totalt genomfördes fyra optimeringsprocesser, där 975 kanaler evaluerades, varav den förstaoptimeringen skedde på en något modifierad test-kanal som verifikationssteg, medan de senareoptimeringarna skedde på FOI-kanalen. Två optimeringar genomfördes på marschhöjdsförhållanden på 11km höjd, medan resterande optimeringar genomfördes för start-förhållandenpå standard havsnivå. Metoden gav goda resultat, med maximalt 52,8% relativ minskning av flödesdistorsionenmedan tryckåtervinsten bibehölls inom 0.06% av ursprungliga värdet. Det framgick att metodengav störst förbättring för fallet vid marschhöjd, jämfört med originalkanalen. Det påpekades också att den implementerade metoden har begränsningar och är känslig förkraftiga separationer och flödesinstabiliteter, vilket kan skapa oscillationer i lösaren och därmedge falska resultat. Det påverkade den tredje optimeringsprocessen där den optimala lösningenvar okonvergerad, och därmed inte gav verklig förbättring av kanalens prestanda

Context: This thesis deals with the robustness testing of web applications on a different web browser using a Selenium WebDriver to automate the browser. To increase the efficiency of this automation testing, we are using a robustness method. Robustness method is a process of testing the behaviour of a system implementation under exceptional execution conditions to check if it still fulfils some robustness requirements. These robustness tests often apply random algorithms to select the actions to be executed on web applications. The search-based technique was used to automatically generate effective test cases, consisting of initial conditions and fault sequences. The success criteria in most cases: "if it does not crash or hang application, then it is robust". Problem: Software testing consumes a lot of time, labour-intensive to write test cases and expensive in a software development life cycle. There was always a need for software testing to decrease the testing time. Manual testing requires a lot of effort and hard work if we measure in terms of person per month [1]. To overcome this problem, we are using a search-based approach for robustness testing of web applications which can dramatically reduce the human effort, time and the costs related to testing. Objective: The purpose of this thesis is to develop an automated approach to carry out robustness testing of web applications focusing on revealing defects related to a sequence of events triggered by a web system. To do so, we will employ search-based techniques (e.g., NSGA-II algorithm [1]). The main focus is on Ericsson Digital BSS systems, with a special focus on robustness testing. The main purpose of this master thesis is to investigate how automated robustness testing can be done so that the effort of keeping the tests up to date is minimized when the functionality of the application changes. This kind of automation testing is well depended on the structure of the product being tested. In this thesis, the test object was structured in a way, which made the testing method simple for fault revelation and less time-consuming. Method: For this approach, a meta-heuristic search-based genetic algorithm is used to make efficiency for robustness testing of the web application. In order to evaluate the effectiveness of this proposed approach, the experimental procedure is adapted. For this, an experimental testbed is set up. The effectiveness of the proposed approach is measured by two objectives: Fault revelation, Test sequence length. The effectiveness is also measured by evaluating the feasible cost-effective output test cases. i Results:The results we collected from our approach shows that by reducing the test sequence length we can reduce the time consuming and by using the NSGA-2 algorithm we found as many faults as we can when we tested on web applications in Ericsson. Conclusion: The attempt of testing of web applications, was partly succeeded. This kind of robustness testing in our approach was strongly depended on the algorithm we are using. We can conclude that by using these two objectives, we can reduce the cost of testing and time consuming.

Este trabalho é referente ao desenvolvimento de um calibrador multiobjetivo automático do modelo SWMM (Storm Water Management Model), e avaliação de algumas fontes de incertezas presentes no processo de calibração, visando à representação satisfatória da transformação chuva-vazão. O código foi escrito em linguagem C, e aplica os conceitos do método de otimização multiobjetivo NSGAII (Non Dominated Sorting Genetic Algorithm) com elitismo controlado, além de utilizar o código fonte do modelo SWMM para a determinação das vazões simuladas. Paralelamente, também foi criada uma interface visual, para melhorar a facilidade de utilização do calibrador. Os testes do calibrador foram aplicados a três sistemas diferentes: um sistema hipotético disponibilizado no pacote de instalação do SWMM; um sistema real de pequenas dimensões, denominado La Terraza, localizado no município de Sierra Vista, Arizona (EUA); e um sistema de maiores dimensões, a bacia hidrográfica do Córrego do Gregório, localizada no município de São Carlos (SP). Os resultados indicam que o calibrador construído apresenta, em geral, eficiência satisfatória, porém é bastante dependente da qualidade dos dados observados em campo e dos parâmetros de entrada escolhidos pelo usuário. Foi demonstrada a importância da escolha dos eventos utilizados na calibração, do estabelecimento de limites adequados nos valores das variáveis de decisão, da escolha das funções objetivo e, principalmente, da qualidade e representatividade dos dados de monitoramento pluvio e fluviométrico. Conclui-se que estes testes desenvolvidos contribuem para o entendimento mais aprofundado dos processos envolvidos na modelagem e calibração, possibilitando avanços na confiabilidade dos resultados da modelagem. / This project refers to the development of an automatic multi-objective calibrator for the SWMM (Storm Water Management Model), and the evaluation of some uncertainties sources inherent to the calibration process, aiming to a satisfactory rainfall-runoff transformation representation. The code was written in C language, and applies the concepts of the multi-objective optimization method NSGAII (Non Dominated Sorting Genetic Algorithm) with controlled elitism, using the source code of SWMM to calculate the simulated flow. In addition, a visual interface was also created to improve the calibrators usability. The calibrator tests were applied to three different systems: a hypothetical system available in the SWMM installation package; a real system of small dimensions, called La Terraza, located in the city of Sierra Vista, Arizona (USA); and a large dimensions system, the watershed of Gregório Stream, located in São Carlos (SP). The results indicate that the calibrator built presents, in general, satisfactory efficiency, although it is very dependent on the observed data quality and the input parameters selected by the user. The importance of the events chosen for calibration, the settlement of appropriate limits on the decision variables values, the objective functions choice, and especially the quality and representativeness of the rainfall and runoff monitoring data were demonstrated. We conclude that these performed tests contribute to the thorough understanding of the processes involved in modeling and calibration, enabling advances in the modeling results reliability.

Este trabalho é referente ao desenvolvimento de um calibrador multiobjetivo automático do modelo SWMM (Storm Water Management Model), e avaliação de algumas fontes de incertezas presentes no processo de calibração, visando à representação satisfatória da transformação chuva-vazão. O código foi escrito em linguagem C, e aplica os conceitos do método de otimização multiobjetivo NSGAII (Non Dominated Sorting Genetic Algorithm) com elitismo controlado, além de utilizar o código fonte do modelo SWMM para a determinação das vazões simuladas. Paralelamente, também foi criada uma interface visual, para melhorar a facilidade de utilização do calibrador. Os testes do calibrador foram aplicados a três sistemas diferentes: um sistema hipotético disponibilizado no pacote de instalação do SWMM; um sistema real de pequenas dimensões, denominado La Terraza, localizado no município de Sierra Vista, Arizona (EUA); e um sistema de maiores dimensões, a bacia hidrográfica do Córrego do Gregório, localizada no município de São Carlos (SP). Os resultados indicam que o calibrador construído apresenta, em geral, eficiência satisfatória, porém é bastante dependente da qualidade dos dados observados em campo e dos parâmetros de entrada escolhidos pelo usuário. Foi demonstrada a importância da escolha dos eventos utilizados na calibração, do estabelecimento de limites adequados nos valores das variáveis de decisão, da escolha das funções objetivo e, principalmente, da qualidade e representatividade dos dados de monitoramento pluvio e fluviométrico. Conclui-se que estes testes desenvolvidos contribuem para o entendimento mais aprofundado dos processos envolvidos na modelagem e calibração, possibilitando avanços na confiabilidade dos resultados da modelagem. / This project refers to the development of an automatic multi-objective calibrator for the SWMM (Storm Water Management Model), and the evaluation of some uncertainties sources inherent to the calibration process, aiming to a satisfactory rainfall-runoff transformation representation. The code was written in C language, and applies the concepts of the multi-objective optimization method NSGAII (Non Dominated Sorting Genetic Algorithm) with controlled elitism, using the source code of SWMM to calculate the simulated flow. In addition, a visual interface was also created to improve the calibrators usability. The calibrator tests were applied to three different systems: a hypothetical system available in the SWMM installation package; a real system of small dimensions, called La Terraza, located in the city of Sierra Vista, Arizona (USA); and a large dimensions system, the watershed of Gregório Stream, located in São Carlos (SP). The results indicate that the calibrator built presents, in general, satisfactory efficiency, although it is very dependent on the observed data quality and the input parameters selected by the user. The importance of the events chosen for calibration, the settlement of appropriate limits on the decision variables values, the objective functions choice, and especially the quality and representativeness of the rainfall and runoff monitoring data were demonstrated. We conclude that these performed tests contribute to the thorough understanding of the processes involved in modeling and calibration, enabling advances in the modeling results reliability.