Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-07-17T13:14:38Z No. of bitstreams: 1 FranciscaDeFatimaDoNascimentoSilva_TESE.pdf: 4413362 bytes, checksum: e0033cfcbd51c0cdcb5f93d10f64d5d3 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-07-19T11:55:55Z (GMT) No. of bitstreams: 1 FranciscaDeFatimaDoNascimentoSilva_TESE.pdf: 4413362 bytes, checksum: e0033cfcbd51c0cdcb5f93d10f64d5d3 (MD5) / Made available in DSpace on 2017-07-19T11:55:56Z (GMT). No. of bitstreams: 1 FranciscaDeFatimaDoNascimentoSilva_TESE.pdf: 4413362 bytes, checksum: e0033cfcbd51c0cdcb5f93d10f64d5d3 (MD5) Previous issue date: 2017-03-06 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / O desenvolvimento de um campo petrol?fero pode ser entendido como o conjunto de a??es necess?rias para colocar o campo em produ??o: perfura??es, sistemas de inje??o, plataformas, etc. A forma como ser? feito este desenvolvimento define uma ou mais alternativas. Assim, definir alternativas de desenvolvimento de um campo petrol?fero ? uma das tarefas mais importantes na ?rea de reservat?rios, dado que estas defini??es afetam o comportamento do reservat?rio, decis?es futuras, an?lises econ?micas e, consequentemente, a atratividade resultante dos projetos definidos. Este trabalho apresenta a implementa??o de um sistema otimizador multiobjetivo baseado no algoritmo gen?tico NSGA-II (Non-Dominated Sorting Genetic Algorithm), que oferece uma ferramenta de suporte ? decis?o e automatiza a busca de alternativas para o desenvolvimento de campos petrol?feros submetidos ao processo de inje??o de ?gua. Cada alternativa refere-se ? forma como um campo petrol?fero, conhecido e delimitado, ? colocado em produ??o, isto ?, diz respeito ? determina??o do n?mero e a disposi??o dos po?os produtores e injetores no campo. A aplica??o do algoritmo consiste em encontrar as configura??es de produ??o que, em longo prazo, forne?am o maior Valor Presente L?quido (VPL), obtido a partir do custo de investimento inicial, do pre?o do petr?leo, da produ??o de ?leo e dos custos de opera??o pagos durante o tempo de produ??o, ou seja, a condi??o operacional mais vi?vel economicamente, reduzindo o tempo do processo de tomada de decis?o. Com os resultados apresentados foi poss?vel observar que em v?rios casos as aplica??es das linhas de a??o possibilitaram aumentos significativos no VPL e no Fator de Recupera??o ao final do projeto. Considerando o Caso_36 de dimens?o de malha de 300m, o Fator de Recupera??o aumentou de 45,66% para 50,24%, um aumento de quase 5 pontos percentuais no volume de ?leo recuperado. Diante do exposto, observa-se que as interven??es operacionais de alterar (aumentar ou diminuir) a vaz?o de inje??o de ?gua inicial ou mudar o layout de malha no campo melhoram a rentabilidade, reduzindo os custos com a inje??o de ?gua, tratamento e descarte da ?gua produzida, aumentando o tempo de viabilidade do projeto. Por outro lado, ? importante destacar tamb?m que, em alguns casos, ao aplicar as linhas de a??o, o Fator de recupera??o final ? menor, mas ainda sim as redu??es dos custos operacionais viabilizam a opera??o. / The development of an oil field can be understood as the set of actions necessary to put the field into production: drilling, injection systems, platforms, etc. This development the way will be made defines an alternative. Set a development of an oil field alternative is one of the most important tasks in the reservoir area, given that this definition affects the reservoir behavior, future decisions, economic analysis and consequently the resulting attractiveness of the defined project. This paper presents the implementation of a system based on genetic algorithm multiobjective optimizer NSGA-II (Non-Dominated Sorting Genetic Algorithm), which offers a decision support tool and automates the search for alternatives to the development of the oilfield submitted to water injection process. Each alternative refers to how an oil field, known and defined, is put into production, that is, with respect to the determination of number and the disposition of producers wells and injectors in the field. The implementation of the algorithm is to find the production settings, in the long run, which provide the highest net present value (NPV), obtained from the initial investment cost, the price of oil, oil production and operation costs paid during the production time, considering the operational conditions economically viable, reducing operating costs and the time in the decision-making process. With the obtained results it was possible to observe that in many cases the application of the lines of action enabled relevant rise on the net present value (NPV) and also in the Recovery Factor, both seen in the end of the project. Considering the Case_36 of the mesh that has 300m, the Recovery Factor increased from 45,66% to 50,24%, a rise of almost 5 percentage points on the volume of oil recovered. In the light of what was presented, it may be perceived that the operations that alter (ascending or descending) the flow of water injection or that change the mesh?s layout on the field improve the profitability, reducing costs from the water injection, treatment and disposal of the produced water, increasing the duration of viability of the project. However, it is important to highlight that, in some cases, applying the lines of action, the final recovery factor is lower, but still the reductions of the operational costs will make the operation viable.

O presente trabalho otimizou os parâmetros concentrados do sistema de suspensão de um modelo de veículo completo, representando um automóvel de passeio que trafega a uma velocidade constante por um determinado perfil de pista previsto na norma ISO 8608, 1995, através da utilização de um algoritmo meta-heurístico de otimização multiobjetivo. Duas rotinas numérico-computacionais foram desenvolvidas, visando realizar tal otimização tanto no domínio do tempo quanto no domínio da frequência. A utilização de algoritmos meta-heurísticos vem ganhando espaço na otimização de sistemas mecânicos, proporcionando rapidez e precisão na obtenção de resultados ótimos. Ao se combinar um algoritmo de otimização a um modelo que represente satisfatoriamente um sistema mecânico, obtém-se uma ferramenta indicadora dos parâmetros de máxima eficiência do sistema, que pode ser utilizada em inúmeras aplicações. Pretendeu-se, com a integração de rotinas de análise dinâmica nos domínios do tempo e da frequência ao algoritmo genético de otimização multiobjetivo NSGA-II, desenvolvido por Deb et al., 2002, a obtenção de duas fronteiras ótimas de Pareto. Estas fronteiras consistem no conjunto de soluções não dominadas que minimizam as seguintes funções objetivo: o valor RMS ponderado da aceleração vertical do assento do motorista, o valor RMS da média do fator de amplificação dinâmica das quatro rodas do modelo e o máximo deslocamento relativo entre cada roda e a carroceria. O método proposto por Shinozuka e Jan, 1972, é utilizado para a obtenção do perfil de irregularidades da pista no domínio do tempo a partir das equações de densidade espectral de potência (PSD) que representam as diferentes classes de pavimentos. O método de Newmark, 1959, é utilizado para resolver a equação diferencial de movimento no domínio do tempo e obter a resposta dinâmica do modelo a tais irregularidades. O comportamento dinâmico do modelo de veículo no domínio da frequência foi obtido através da utilização da função de resposta em frequência (FRF) do modelo de veículo analisado. Os resultados demonstraram a capacidade de ambas as rotinas de análise dinâmica desenvolvidas de produzir resultados consistentes com os encontrados na literatura, bem como a capacidade dos algoritmos de otimização implementados de fornecer fronteiras ótimas de Pareto para os problemas propostos. / The proposed work optimized the concentrated parameters of a full-vehicle model’s suspension system, being that model representative of a passenger car which travels at a constant speed on a certain road profile provided by the ISO 8608, 1995, standard, using a multi-objective meta-heuristic optimization algorithm. Two numerical-computational routines were developed, seeking to perform said optimization for both the time and frequency domains. The use of meta-heuristic algorithms has been increasing in mechanical systems optimization, providing speed and accuracy in obtaining an optimal result. Combining an optimization algorithm with a model that satisfactorily represents a mechanical system yields a tool that indicates the system’s maximum efficiency parameters, which can be used in numerous applications. It was intended, with the integration of the dynamic analysis routines to the multi-objective genetic optimization algorithm NSGA-II, developed by Deb et al., 2002, the obtainment of two Pareto-optimal fronts. These fronts consist in the set of non-dominated solutions that minimize the following objective functions: the weighted RMS value of the driver’s seat vertical acceleration, the mean RMS value of the model wheel’s dynamic amplification factor, and the maximum relative displacement between each wheel and the body of the vehicle model. The method proposed by Shinozuka and Jan, 1972, is used to obtain the road irregularity profile in the time domain from the power spectral density (PSD) equations that represent the different pavement classes. The Newmark’s method (1959) is used to solve the differential motion equation in the time domain, in order to obtain the vehicle model’s responses to these irregularities. The dynamic behavior of the vehicle model in the frequency domain was obtained through the use of the frequency response function (FRF) of the analyzed model. The results showed the capacity of both the dynamic analysis routines developed in generating results that are consistent with those found in literature, as well as the capacity of the optimization algorithms implemented in providing Pareto optimal fronts to the proposed problems.

This master thesis focuses on approximate computing applied to image processing. Specifically, the approximation is applied to adaptive thresholding. Two approaches were used, the design of a new system using approximated components and the approximation of an existing algorithm. The resulting effect on thresholding quality was investigated. Experimental evaluation of the first approach shows quality improvements of thresholding with usage of aproximated components. Also, area of found aproximated solutions is smaller. Evaluation of the second approach shows worse quality of thresholding with usage of aproximated components. The second approach is then declared inappropriate.

This thesis is focused on working up evolutionals and genetics algorithms issues Especially for multiobjective algorithms VEGA, SPEA and NSGA – II. Thereinafter one of FrameWork working with genetics algorithms namely WWW NIMBUS. From this mentioned algorithms was selected VEGA algorithm for implementation in JAVA to preselected problem. Thereby problem is choice thick columns of profile according to predetermined criteria. Selected algorithm works on division of population into several groups and each group evaluates the resulting fitness function. Here is a sample implementation of this algorithm. Furthermore there is a example of working with FrameWork. In the next section are compared the results of generated progam with results that were obtained by FrameWork WWW NIMBUS. As for VEGA, and the Nimbus there are shown different results. The VEGA is presented also the development of individual fitness functions. Also, there are shown graphs, that can be obtained from NIMBUS. At the end of work is introduced the comparation of the results ane propose possible improvements.

Connected and automated vehicles (CVs and AVs, respectively) are rapidly emerging paradigms aiming to deploy and develop transportation systems that enable automated driving and data exchange among vehicles, infrastructure, and mobile devices to improve mobility, enhance safety, and reduce the adverse environmental impacts of transportation systems. Based on these premises, the focus of this research is to quantify the potential benefits of CVs and AVs to provide insight into how these technologies will impact road users and network performance. To assess the traffic operational performance of CVs, a connectivity-based modeling framework was developed based on traffic microsimulation for a real network in the city of Toronto. Then the effects of real-time routing guidance and advisory warning messages were studied for CVs. In addition, the impact of rerouting of non-connected vehicles (non-CVs) in response to various sources of information, such as mobile apps, GPS or VMS, was considered and evaluated. The results demonstrate the potential of such systems to improve mobility, enhance safety, and reduce greenhouse gas emissions (GHGs) at the network-wide level presented for different CVs market penetration. Additionally, the practical application of CVs in travel time estimation and its relationship with the number and location of roadside equipment (RSE) along freeways was investigated. A methodology was developed for determining the optimal number and location of roadside equipment (RSE) for reducing travel time estimation error in a connected vehicle environment. A simulation testbed that includes CVs was developed and implemented in the microsimulation model for Toronto 400-series highway network. The results reveal that the suggested methodology is capable of optimizing the number and location of RSEs in a connected vehicle environment. The optimization results indicate that the accuracy of travel time estimates is primarily dependent on the location of RSEs and less dependent on the total density of RSEs. In addition to CVs, the potential capacity increase of highways as a function of AVs market penetration was also studied and estimated. AVs are classified into Cooperative and Autonomous AVs. While Autonomous AVs rely only to their detection technology to sense their surroundings, Cooperative AVs, can also benefit from direct communication between vehicles and infrastructure. Cooperative car-following and lane-changing models were developed in a microsimulation model to enable AVs to maintain safe following and merging gaps. This study shows that cooperative AVs can adopt shorter gap than autonomous AVs and consequently, can significantly improve the lane capacity of highways. The achievable capacity increase for autonomous AVs appears highly insensitive to the market penetration, namely, the capacity remains within a narrow range of 2,046 to 2,238 vph irrespective of market penetration. The results of this research provide practitioners and decision-makers with knowledge regarding the potential capacity benefits of AVs with respect to market penetration and fleet conversion. / Thesis / Doctor of Philosophy (PhD)

Due to the high cost of manual content creation within the game development industry, methods for procedural generation of content such as game maps and levels have emerged. However, methods for generating game maps have remained relatively unexplored in competitive multiplayer contexts. Presumably, this is due to the opposing goals of generating game maps that are both interesting and fair. This study aims to explore the possibility of satisfying both these goals simultaneously by separating the generative phase from the phase that enforces fairness. In this endeavor, simple game maps for a generic multiplayer grand strategy game are generated using noise-based methods. The task of partitioning the game map fairly between the players is then modeled as a constrained categorical multiobjective minimization problem that is subsequently solved by two genetic algorithms, the reference-point-based algorithm NSGA-III and the decomposition-based algorithm MOEA/D-IEpsilon. In a primary study, the proposed partitioning method is evaluated based on the quality of the solutions produced, its scalability, and its ability to find symmetrical partitions of symmetrical game maps. The results show that the proposed method makes significant improvement from the initial guess but fails to produce completely fair partitions in general. Explanations and possible solutions to this are presented. The timing results indicate that the proposed method is not applicable in real-time contexts. However, the proposed method might still be applicable in online contexts if smaller game maps are considered and in offline contexts if larger game maps are considered. Finally, the partitioning results show that the proposed method successfully finds fair partitions of symmetrical game maps but fails to find the obvious symmetrical partitions. In a secondary study, the two genetic algorithms are compared to determine which algorithm produces dominating solutions and which algorithm produces most diverse solution. The results indicate that, for the partitioning problems considered in this study, the reference-point-based algorithm is both dominant and produces the most diverse solutions.

This thesis tackles the topic of serving IoT applications in the computing continuum. It proposes an approach to place applications in the tiers of the continuum, considering latency and energy as predefined metrics. It presents a system model to represent the computing continuum environment, and then, defines an optimization function that is tailored to meet the specific requirements of the IoT applications. The optimization function addresses the relationship between latency and energy consumption in the framework of IoT service provision, and it is implemented in two different directions: (1) the first direction uses a modified Genetic algorithm, and (2) the second direction utilizes the Machine learning concept. To evaluate the performance of the proposed approach, we incorporate different testbed setups and network configurations. All the setups and configurations are designed to represent the diverse demands of IoT applications. Then, different algorithms (such as Non-dominated Sorting Genetic Algorithm (NSGA), Brute Force, and Machine Learning) are implemented to provide different application placement scenarios. The results highlight the efficiency of the proposed approach in comparison with the Brute Force optimal solution while meeting the application requirements. This thesis proposes an optimized solution for serving IoT applications in the computing continuum environment. It considers two essential metrics (latency and energy consumption) in the applications placement processes while meeting the diverse functional and non-functional requirements of these applications. The study provides insights and ideas for future research to refine strategies that will minimize latency and energy consumption. It also urges researchers to consider more metrics while developing and implementing IoT applications. The requirements related to computing resources and performance levels make the development and implementation of these applications complex and challenging. This study serves as a foundational stepping stone towards addressing those challenges.

Made available in DSpace on 2014-06-12T17:36:41Z (GMT). No. of bitstreams: 2 arquivo9409_1.pdf: 2593707 bytes, checksum: c82123beb5138e539b7e5a7a30279094 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2012 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Nesta Tese são propostas diversas estratégias para projetar redes ópticas WDM de forma otimizada. As redes são consideradas com tráfego dinâmico e penalizadas pelas penalidades da camada física. As estratégias propostas lidam com os principais elementos que afetam a relação custo desempenho em uma rede óptica: o algoritmo de roteamento e atribuição de comprimentos de onda (RWA), a colocação de regeneradores (RP), a atribuição de regeneradores (RA), o projeto da topologia física da rede (PTD) e o dimensionamento dos dispositivos ópticos (DDO) que serão instalados na rede. Esses problemas são tratados tanto de forma separada quanto de forma integrada na Tese. Para o RWA, é proposta uma metodologia para se projetar algoritmos heurísticos de roteamento que têm como objetivo o aumento no desempenho da rede e que levam em conta as penalidades da camada física. Para a solução do RP são propostos algoritmos heurísticos e metaheurísticos para o projeto de redes ópticas translúcidas, considerando simultaneamente a otimização dos custos de capital (CapEx) e operacional (OpEx) e do desempenho da rede. O problema de PTD é tratado em conjunto com o DDO também de forma mutiobjetiva, considerando a otimização simultânea do CapEx e do desempenho (probabilidade de bloqueio). Um algoritmo multiobjetivo para realização da expansão de topologia (i.e. adição de novos enlaces a uma rede já existente) também é proposto. Além disso, são resolvidos conjuntamente os problemas de PTD, RP e RWA de forma mutiobjetiva considerando a otimização simultânea de CapEx e desempenho da rede. As otimizações das soluções são feitas utilizando as seguintes estratégias metaheuristicas propostas na área de inteligência computacional: Particle Swarm Optimization (PSO) e Non-dominated Sorting Genetic Algorithm II (NSGA-II)

This paper presents the study of Parallel Multiobjective Evolutionary Algorithms to enable the automation of exterior lighting designs by computers and results in an optimized version of the algorithm. The resulting algorithm basically works with variable length chromosomes and for which intrinsic operators of crossover and mutation were created. The fitness function was determined through a statistical evaluation method (difference of means), thus enabling the comparison of how different options of fitness functions could impact the performance of the proposed parallel multi-objective evolutionary algorithm. The chosen fitness function enables to develop more efficiently automated designs for exterior lighting. Moreover, adding to the proposed evolutionary algorithm, an application was developed in which the user chooses which the heights of the poles, lamps and fixtures to use and also the layout of the area to be illuminated (allowed to be irregular). Within this area, can be defined sub-areas where there are restrictions on the placement of lighting poles. The user must be set average illumination with a respective tolerance range, though. As a case study, the area of an airport parking lot in the city of Uberlândia-MG (Brazil) is presented. Evolved designs present a low coefficient of variation evaluated for 30 runs. This demonstrates that the system is converging on designs for similar metrics. By identifying the worst and the best of designs achieved by the system for those executions, one could note that there are savings regarding installed capacity when compared to the design of reference: 37.5 % for the worst evolved design and 50.0 % for the best evolved design. Also, evolved designs have better lighting uniformity and energy efficiency, as well as their respective quantities of lighting poles have decreased. / Este trabalho apresenta o estudo de um Algoritmo Evolucionário Multiobjetivo Paralelo que viabiliza a criação de projetos de iluminação de áreas externas automatizadas por computador e que resulta em uma versão otimizada desse algoritmo. O algoritmo resultante, essencialmente, trabalha com cromossomos de tamanho variável e para os quais foram criados operadores intrínsecos de cruzamento e mutação. A determinação da função de aptidão ocorreu por meio do método de avaliação estatística (diferença de médias), possibilitando, assim, a comparação de diferentes opções das funções de aptidão no desempenho do algoritmo evolucionário multiobjetivo paralelo proposto. Com a função escolhida, tornou-se possível construir projetos automatizados de iluminação externa de forma mais eficiente. Além disso, por meio do algoritmo evolucionário proposto, foi desenvolvida uma aplicação, pela qual o usuário escolhe quais as alturas dos postes, lâmpadas e luminárias que deseja utilizar e também o layout de área a ser iluminada (mesmo que irregular). Dentro dessa área, podem ser definidas subáreas onde existem restrições quanto à colocação de postes de iluminação. O usuário deve definir a iluminação média associada à sua respectiva tolerância, ou faixa de variação. Como estudo de caso, é apresentada a área de um estacionamento do aeroporto da cidade de Uberlândia, MG. Os projetos desenvolvidos, apresentam um baixo coeficiente de variação calculado a partir de 30 execuções. Isso demonstra que o sistema está convergindo para projetos com métricas similares. Ao identificar o pior e o melhor dos projetos apresentados como solução pelo sistema para essas execuções, pode-se notar que apresentam economia nas potências instaladas quando comparados ao projeto de referência: 37,5% no pior dos projetos e 50% no melhor projeto apresentado. Além disso, constataram-se melhores uniformidades para iluminação e maiores eficiências energéticas, bem como a diminuição das respectivas quantidades de unidades de iluminação. / Doutor em Ciências

Submitted by Eduarda Figueiredo (eduarda.ffigueiredo@ufpe.br) on 2015-03-06T13:44:05Z No. of bitstreams: 2 chaves.pdf: 2856967 bytes, checksum: 08cd733e8cb84a531adc13230e5edaaf (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-06T13:44:05Z (GMT). No. of bitstreams: 2 chaves.pdf: 2856967 bytes, checksum: 08cd733e8cb84a531adc13230e5edaaf (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2012-02-24 / CNPq e CAPES / Nesta Tese são propostas diversas estratégias para projetar redes ópticas WDM de forma otimizada. As redes são consideradas com tráfego dinâmico e penalizadas pelas penalidades da camada física. As estratégias propostas lidam com os principais elementos que afetam a relação custo desempenho em uma rede óptica: o algoritmo de roteamento e atribuição de comprimentos de onda (RWA), a colocação de regeneradores (RP), a atribuição de regeneradores (RA), o projeto da topologia física da rede (PTD) e o dimensionamento dos dispositivos ópticos (DDO) que serão instalados na rede. Esses problemas são tratados tanto de forma separada quanto de forma integrada na Tese. Para o RWA, é proposta uma metodologia para se projetar algoritmos heurísticos de roteamento que têm como objetivo o aumento no desempenho da rede e que levam em conta as penalidades da camada física. Para a solução do RP são propostos algoritmos heurísticos e metaheurísticos para o projeto de redes ópticas translúcidas, considerando simultaneamente a otimização dos custos de capital (CapEx) e operacional (OpEx) e do desempenho da rede. O problema de PTD é tratado em conjunto com o DDO também de forma mutiobjetiva, considerando a otimização simultânea do CapEx e do desempenho (probabilidade de bloqueio). Um algoritmo multiobjetivo para realização da expansão de topologia (i.e. adição de novos enlaces a uma rede já existente) também é proposto. Além disso, são resolvidos conjuntamente os problemas de PTD, RP e RWA de forma mutiobjetiva considerando a otimização simultânea de CapEx e desempenho da rede. As otimizações das soluções são feitas utilizando as seguintes estratégias metaheuristicas propostas na área de inteligência computacional: Particle Swarm Optimization (PSO) e Non-dominated Sorting Genetic Algorithm II (NSGA-II).