As metodologias normalmente utilizadas para otimizar as dimensões de uma usina hidroelétrica, incluindo os métodos empregados pelo Setor Elétrico Brasileiro, baseiam-se em análises do tipo custo/benefício. Os custos provêm de gastos diretos com a construção da usina e os benefícios correspondem a receitas proporcionadas pela venda de energia. Para avaliar os benefícios, são realizadas simulações da operação da usina e a energia produzida é valorizada economicamente. Esta necessidade das simulações da operação faz com que o problema de dimensionamento não possua uma função analítica explícita para determinar os benefícios energéticos, o que dificulta a implementação de métodos tradicionais de otimização. O objetivo deste trabalho é justamente desenvolver e implementar uma metodologia de dimensionamento que permita que o processo de busca pelas dimensões ótimas seja automático. Para tanto, acoplam-se um modelo de otimização evolutiva e um modelo de simulação da operação de sistemas hidroelétricos. Adicionalmente, o modelo proposto também deve ser flexível, permitindo que as regras de operação do sistema hidroelétrico, o conjunto de vazões afluentes, a forma de valorização da energia gerada e uma série de outros fatores sejam tratados como parâmetros do modelo. Os resultados encontrados indicam que, sob o ponto de vista computacional, o modelo proposto é automático, flexível e eficiente. Além disso, as várias análises de sensibilidade realizadas atestam a consistência da metodologia proposta e permitem avaliar a forma como os diferentes parâmetros do modelo influenciam as próprias dimensões da usina sob dimensionamento. A partir destas análises, sugerem-se algumas medidas de regulamentação e planejamento para que as dimensões de novas usinas não sejam determinadas a partir de sinalizações imprecisas de parâmetros que influenciam de forma decisiva suas dimensões ótimas. / The methods normally applied to optimally size a hydropower plant, including the ones used by the Brazilian Power Industry, are based on cost/benefit analysis. The costs are due to direct expenses with the hydropower plant construction and the benefits correspond to incomes from selling energy. The benefits are evaluated throughout computing simulations of the hydropower plant operation, followed by the assignment of an economical value to the energy produced by it. The need for computing simulations turns out a non-analytical objective function for the sizing problem, what makes the use of traditional optimization tools very hard. The objective of this work is just to develop and implement a sizing method that automatically performs the search for the optimal sizes of a hydropower plant. The proposed method combines an evolutionary optimization technique and a simulation model for the operation of hydropower systems. Additionally, the proposed model is also flexible in the sense that the operation rules for the hydroelectric system simulation, the set of water inflows, the way the energy is valued and some other factors that may influence the results are treated as parameters. The results show that, from the computing point of view, the proposed method is automatic, flexible and efficient. Furthermore, the sensitivity analyses performed validate the method consistency and establish relationships among the different parameters and the way they affect the optimal features of the new hydropower plant. Based on the results of such analyses, some regulation and planning measures are suggested in order to avoid sizing hydropower plants with mistaken parameters that can substantially change its optimal features.

The surveillance of geographic borders and critical infrastructures using limited sensor capability has always been a challenging task in many homeland security applications. While geographic borders may be very long and may go through isolated areas, critical assets may be large and numerous and may be located in highly populated areas. As a result, it is virtually impossible to secure each and every mile of border around the country, and each and every critical infrastructure inside the country. Most often, a compromise must be made between the percentage of border or critical asset covered by surveillance systems and the induced cost. Although threats to homeland security can be conceived to take place in many forms, those regarding illegal penetration of the air, land, and maritime domains under the cover of day-to-day activities have been identified to be of particular interest. For instance, the proliferation of drug smuggling, illegal immigration, international organized crime, resource exploitation, and more recently, modern piracy, require the strengthening of land border and maritime awareness and increasingly complex and challenging national security environments. The complexity and challenges associated to the above mission and to the protection of the homeland may explain why a methodology enabling the design and optimization of distributed detection systems architectures, able to provide accurate scanning of the air, land, and maritime domains, in a specific geographic and climatic environment, is a capital concern for the defense and protection community. This thesis proposes a methodology aimed at addressing the aforementioned gaps and challenges. The methodology particularly reformulates the problem in clear terms so as to facilitate the subsequent modeling and simulation of potential operational scenarios. The needs and challenges involved in the proposed study are investigated and a detailed description of a multidisciplinary strategy for the design and optimization of detection architectures in terms of detection performance and cost is provided. This implies the creation of a framework for the modeling and simulation of notional scenarios, as well as the development of improved methods for accurate optimization of detection architectures. More precisely, the present thesis describes a new approach to determining detection architectures able to provide effective coverage of a given geographical environment at a minimum cost, by optimizing the appropriate number, types, and locations of surveillance and detection systems. The objective of the optimization is twofold. First, given the topography of the terrain under study, several promising locations are determined for each sensor system based on the percentage of terrain it is covering. Second, architectures of sensor systems able to effectively cover large percentages of the terrain at minimal costs are determined by optimizing the number, types and locations of each detection system in the architecture. To do so, a modified Genetic Algorithm and a modified Particle Swarm Optimization are investigated and their ability to provide consistent results is compared. Ultimately, the modified Particle Swarm Optimization algorithm is used to obtain a Pareto frontier of detection architectures able to satisfy varying customer preferences on coverage performance and related cost.

As metodologias normalmente utilizadas para otimizar as dimensões de uma usina hidroelétrica, incluindo os métodos empregados pelo Setor Elétrico Brasileiro, baseiam-se em análises do tipo custo/benefício. Os custos provêm de gastos diretos com a construção da usina e os benefícios correspondem a receitas proporcionadas pela venda de energia. Para avaliar os benefícios, são realizadas simulações da operação da usina e a energia produzida é valorizada economicamente. Esta necessidade das simulações da operação faz com que o problema de dimensionamento não possua uma função analítica explícita para determinar os benefícios energéticos, o que dificulta a implementação de métodos tradicionais de otimização. O objetivo deste trabalho é justamente desenvolver e implementar uma metodologia de dimensionamento que permita que o processo de busca pelas dimensões ótimas seja automático. Para tanto, acoplam-se um modelo de otimização evolutiva e um modelo de simulação da operação de sistemas hidroelétricos. Adicionalmente, o modelo proposto também deve ser flexível, permitindo que as regras de operação do sistema hidroelétrico, o conjunto de vazões afluentes, a forma de valorização da energia gerada e uma série de outros fatores sejam tratados como parâmetros do modelo. Os resultados encontrados indicam que, sob o ponto de vista computacional, o modelo proposto é automático, flexível e eficiente. Além disso, as várias análises de sensibilidade realizadas atestam a consistência da metodologia proposta e permitem avaliar a forma como os diferentes parâmetros do modelo influenciam as próprias dimensões da usina sob dimensionamento. A partir destas análises, sugerem-se algumas medidas de regulamentação e planejamento para que as dimensões de novas usinas não sejam determinadas a partir de sinalizações imprecisas de parâmetros que influenciam de forma decisiva suas dimensões ótimas. / The methods normally applied to optimally size a hydropower plant, including the ones used by the Brazilian Power Industry, are based on cost/benefit analysis. The costs are due to direct expenses with the hydropower plant construction and the benefits correspond to incomes from selling energy. The benefits are evaluated throughout computing simulations of the hydropower plant operation, followed by the assignment of an economical value to the energy produced by it. The need for computing simulations turns out a non-analytical objective function for the sizing problem, what makes the use of traditional optimization tools very hard. The objective of this work is just to develop and implement a sizing method that automatically performs the search for the optimal sizes of a hydropower plant. The proposed method combines an evolutionary optimization technique and a simulation model for the operation of hydropower systems. Additionally, the proposed model is also flexible in the sense that the operation rules for the hydroelectric system simulation, the set of water inflows, the way the energy is valued and some other factors that may influence the results are treated as parameters. The results show that, from the computing point of view, the proposed method is automatic, flexible and efficient. Furthermore, the sensitivity analyses performed validate the method consistency and establish relationships among the different parameters and the way they affect the optimal features of the new hydropower plant. Based on the results of such analyses, some regulation and planning measures are suggested in order to avoid sizing hydropower plants with mistaken parameters that can substantially change its optimal features.

La nano-optique est un vaste domaine permettant d'étudier et d'exalter l'interaction lumière-matière à l'échelle nanométrique. Ce domaine couvre notamment la plasmonique, mais depuis quelques années, un effort est porté sur les nanostructures diélectriques à fort indice de réfraction (typiquement des semiconducteurs comme le silicium). Des effets similaires aux nanoparticules plasmoniques peuvent être obtenus, tels un comportement d'antenne et l'exaltation de phénomènes non linéaires (génération d'harmoniques), avec l'avantage de faibles pertes. Dans cette thèse, une analyse des propriétés optiques linéaires et non linéaires de nanostructures individuelles. Une première partie est dédiée aux nanofils de silicium qui supportent de fortes résonances optiques dont le nombre et la gamme spectrale, du proche UV au proche IR, sont fonction de leur diamètre. Dans ces conditions, l'exaltation du champ proche optique et un rapport surface sur volume élevé favorisent l'apparition de processus non linéaires. Ainsi la génération de seconde harmonique (SHG) par rapport au silicium massif est augmentée de deux ordres de grandeur. En outre, différentes contributions à l'origine de la SHG peuvent être adressées individuellement en fonction de la polarisation du laser d'excitation et de la taille des nanofils. Les résultats expérimentaux sont confrontés à des simulations numériques (méthode dyadique de Green, GDM), qui permettent d'identifier les différentes contributions. Dans une seconde partie, la méthode dyadique de Green est couplée à des algorithme évolutionnistes (EO) pour la conception et l'optimisation de propriétés optiques choisies de nanostructures semiconductrices ou métalliques, par exemple diffusion résonnante de différentes longueurs d'ondes pour différentes polarisations.Des échantillons de nanostructures de silicium, réalisés à partir des résultats de l'EO, vérifient avec succès les prédictions de l'algorithme d'optimisation, démontrant l'énorme potentiel de l'EO pour de nombreuses applications en nanophotonique requérant une optimisation simultanée de différents paramètres. / Nano-photonic structures offer a highly interesting platform to enhance light-matter interaction on a nanometer scale. Recently, high-index dielectric structures have gained increasing attention as possible low-loss alternatives to plasmonic nano-antennas made from noble metals. Furthermore, since non-linear effects offer many unique functionalities like the coherent up-conversion of photons, including the generation of harmonics, many efforts are being made to exploit such phenomena in nano-photonics. In this thesis, an analysis is presented on nonlinear optical effects in individual dielectric structures, specifically in silicon nanowires (SiNWs). Nanowires develop strong optical resonances in the visible and infrared spectral range. In this context, strong enhancement of the optical near-field together with a large surface to volume ratio support the appearance of nonlinear effects. We show that, compared to bulk Si, a two orders of magnitude increase in second harmonic generation (SHG) is feasible and furthermore unravel different polarization and size-dependent contributions at the origin of the SHG. Numerical simulations are carried out to reaffirm these experimental findings for which a numerical technique is presented to describe nonlinear effects on the basis of the Green Dyadic Method (GDM). In the last part of the thesis, the GDM is used together with evolutionary optimization (EO) algorithms to tailor and optimize optical properties of photonic nano-structures. We eventually fabricate samples, based on EO design, and successfully verify the predictions of the optimization algorithm. It turns out that EO is an extremely versatile tool and has a tremendous potential for many kinds of further applications in nano-optics.

Tato disertační práce se zabývá evolučním návrhem a optimalizací jak běžných, tak polymorfních digitálních obvodů. V práci jsou uvedena a vyhodnocena nová rozšíření kartézského genetického programování (Cartesian Genetic Programming, CGP), která umožňují zkrácení výpočetního času a získávání kompaktnějších obvodů. Další část práce se zaměřuje na nové metody syntézy polymorfních obvodů. Uvedené metody založené na polymorfních binárních rozhodovacích diagramech a polymorfním multiplexovaní rozšiřují běžné reprezentace digitálních obvodů, a to s ohledem na začlenění polymorfních hradel. Z důvodu snížení počtu hradel v obvodech syntetizovaných uvedenými metodami je provedena evoluční optimalizace založená na CGP. Implementované polymorfní obvody, které jsou optimalizovány s využitím CGP, reprezentují nejlepší známá řešení, jestliže je jako cílové kritérium brán počet hradel obvodu.

Dans un contexte de personnalisation de masse, la configuration concourante du produit et de son processus d’obtention constituent un défi industriel important : de nombreuses options ou alternatives, de nombreux liens ou contraintes et un besoin d’optimisation des choix réalisés doivent être pris en compte. Ce problème est intitulé O-CPPC (Optimization of Concurrent Product and Process Configuration). Nous considérons ce problème comme un CSP (Constraints Satisfaction Problem) et l’optimisons avec des algorithmes évolutionnaires. Un état de l’art fait apparaître : i) que la plupart des travaux de recherche sont illustrés sur des exemples spécifiques à un cas industriel ou académique et peu représentatifs de la diversité existante ; ii) un besoin d’amélioration des performances d’optimisation afin de gagner en interactivité et faire face à des problèmes de taille plus conséquente. En réponse au premier point, ces travaux de thèse proposent les briques d’un modèle générique du problème O-CPPC. Ces briques permettent d’architecturer le produit et son processus d’obtention. Ce modèle générique est utilisé pour générer un benchmark réaliste pour évaluer les algorithmes d’optimisation. Ce benchmark est ensuite utilisé pour analyser la performance de l’approche évolutionnaire CFB-EA. L’une des forces de cette approche est de proposer rapidement un front de Pareto proche de l’optimum. Pour répondre au second point, une amélioration de cette méthode est proposée puis évaluée. L’idée est, à partir d’un premier front de Pareto approximatif déterminé très rapidement, de demander à l’utilisateur de choisir une zone d’intérêt et de restreindre la recherche de solutions uniquement sur cette zone. Cette amélioration entraine des gains de temps de calcul importants. / In a context of mass customization, the concurrent configuration of the product and its production process constitute an important industrial challenge: Numerous options or alternatives, numerous links or constraints and a need to optimize the choices made. This problem is called O-CPPC (Optimization of Concurrent Product and Process Configuration). We consider this problem as a CSP (Constraints Satisfaction Problem) and optimize it with evolutionary algorithms. A state of the art shows that: i) most studies are illustrated with examples specific to an industrial or academic case and not representative of the existing diversity; ii) a need to improve optimization performance in order to gain interactivity and face larger problems. In response to the first point, this thesis proposes a generic model of the O-CPPC problem. This generic model is used to generate a realistic benchmark for evaluating optimization algorithms. This benchmark is then used to analyze the performance of the CFB-EA evolutionary approach. One of the strengths of this approach is to quickly propose a Pareto front near the optimum. To answer the second point, an improvement of this method is proposed and evaluated. The idea is, from a first approximate Pareto front, to ask the user to choose an area of interest and to restrict the search for solutions only on this area. This improvement results in significant computing time savings.

Genetické programování (GP) je v určitém rozsahu schopno automaticky generovat požadované programy, aniž by uživatel musel určit, jakým způsobem má program postupovat. GP bylo s úspěchem použito k řešení široké škály praktických problémů z různých oblastí, přičemž výsledky byly často srovnatelné s řešeními vytvořenými člověkem. Doposud však nebyla zodpovězena otázka, zda GP dokáže generovat vysoce optimalizovaný výpočetní model (platformu) spolu s programem spustitelným na této platformě, který by řešil daný problém při dodržení všech omezení (například na plochu na čipu a zpoždění). V případě scénářů, kdy je optimalizováno více kritérií, by uživatelským výstupem měla být množina nedominovaných řešení s různými kombinacemi úrovně využití zdrojů (plocha, příkon) a výkonu (rychlosti provádění). Tento problém může být chápán jako souběžný návrh hardwaru a softwaru, zkráceně HW/SW codesign. Tato práce zkoumá způsoby, jakými lze souběžně evolučně vyvíjet platformu a programy v případě, že je problém zadán množinou vektorů vstupů a jim odpovídajících výstupů. Nejprve byl vytvořen model architektury a evoluční platforma zajišťující zpracování a evoluční vývoj těchto architektur. Kandidátní mikroprogramové architektury byly evolvovány spolu s programy pomocí lineárního genetického programování. Následně byla provedena série jednodušších experimentů. Navržená platforma dosahovala výsledků srovnatelných s nejnovějšími metodami. Na základě slabých míst objevených během počátečních experimentů byla platforma rozšířena. Rozšířená platforma byla poté ověřena na několika složitějších experimentech. Jeden z nich byla zaměřen na efektivní implementaci aproximace sigmoidální funkce. Platforma v tomto případě našla řadu různých řešení implementujících aproximaci sigmoidy, z nichž některá byla sekvenční a jiná čistě kombinační. V rámci experimentu byly evolučně nalezeny i známé algoritmy, přičemž některé z nich byly evolucí dokonce optimalizovány pro podmnožinu definičního oboru zvolenou pro daný experiment. Poslední sada experimentů byla zaměřena na evoluční návrh obrazových filtrů pro redukci šumu typu sůl a pepř. Platforma v tomto případě znovuobjevila koncept přepínaných filtrů a naezla variantu přepínaného mediánového filtru, která byla z hlediska výsledků filtrace srovnatelná s běžně používanými metodami. Tato práce prokázala, že pomocí genetického programování lze navrhovat a optimalizovat malé HW/SW systémy. Automatizovaný evoluční návrh složitějších HW/SW systémů zůstává otevřeným problémem vhodným k dalšímu výzkumu.

Le concept de l'avion plus électrique a pour but de remplacer les différents types de transmissions de puissance aéronautique par des transmissions électriques. Le réseau électrique doit donc évoluer. Ce concept a inspiré le projet AEROCOTS dont une partie est la modification du moyen de coupure en un contacteur hybridé avec un circuit électrique. Afin de mieux comprendre ce qui se passe aux bornes du contacteur et vérifier qu'il n'y a pas apparition d'arc électrique, une méthode de caractérisation est employée pour obtenir un modèle complet du contacteur paramétré. Deux circuits électriques sont étudiés et l'absence d'un arc est vérifiée. Leur principe est de réduire à zéro le courant avant l'ouverture du contacteur. Leurs fonctionnements et leurs modèles sont vérifiés expérimentalement. Le choix du second circuit est justifié par un contrôle du courant à ouvrir. Une optimisation évolutionnaire, principe de la théorie de Darwin, est réalisée pour répondre aux objectifs aéronautiques / The main goal of the more electrical aircraft is to substitute the different kind of transmission for the aeronautical power by electrical transmissions. The electric network has to evolve. This concept inspires the project AEROCOTS, which a part lies in the modification of the breaking means thanks to a hybrid contactor with an electrical circuit. To better understand what occurs between the contacts of the contactor and verified the absence of an electrical arc, a characterization method is employed to have a complete parameterized model of a contactor. Two electrical circuits are studied and the absence of an arc is verified. Their principle is to reduce to zero the current before the opening of the contactor. Their functioning and their models are experimentally verified. The choice of the second circuit is justified by a control of the opening current. An evolutionary algorithm, principle of the Darwin's theory, is realized to answer to the aeronautical objectives

Diese numerische Arbeit untersucht, wie sich die laminar-turbulente Transition in der Grenzschicht einer ebenen Platte mit elektromagnetischen Kräften verzögern lässt. Erzeugt von einer Elektroden-Magnet-Anordnung in der Platte wirken jene Kräfte im wandnahen Bereich der Strömung. Sie sind wandparallel sowie stromab gerichtet und besitzen zwei Parameter, die Amplitude und die Eindringtiefe. Zwei- und dreidimensionale Direkte Numerische Simulationen, Grenzschichtgleichungslöser sowie lineare Stabilitätsanalyse werden eingesetzt, um zwei Ansätze der Transitionsverzögerung zu verfolgen: Zum einen die aktive Wellenauslöschung, bei der ankommende Grenzschichtinstabilitäten von gegenphasig angeregten Wellen bis zu 97% ausgelöscht werden. Zum anderen können elektromagnetische Kräfte die Grenzschicht beschleunigen und so zu deutlich stabilieren Grenzschichtprofilen führen. Über evolutionäre Optimierung wurde eine räumliche Verteilung von Eindringtiefe und Kraftamplitude gefunden, die den Energieeinsatz minimiert und gleichzeitig laminare Strömung sicherstellt; dennoch bliebt die energetische Effizienz der Beeinflussung unter Eins. / This numerical work investigates how electromagnetic forces may delay laminar-turbulent transition of a flat plate boundary layer. Generated by an array of electrodes and magnets flush mounted in the wall, those forces act within the wall-near flow. They are oriented in wall-parallel, downstream direction and are characterized by two parameters, namely amplitude and penetration depth. Two- and three-dimensional Direct Numerical Simulations, numerical solutions of boundary layer equations and linear stability analysis are applied to study two possible ways of transition delay: first, the so-called active wave cancellation, where an anti-wave cancels incoming boundary layer instabilities by up to 97%. A second option is have electromagnetic forces accelerate the boundary layer, thereby modifying its mean velocity profile for greatly enhanced stability. Using evolutionary optimization, a spatial distribution of force amplitude and penetration depth was obtained that maintains laminar flow while minimizing electrical power consumption of the actuator. However, the energetic efficiency of actuation remains less than unity.

Problems in the control and identification of structural dynamic systems can lead to multimodal optimization problems, which are difficult to solve using classical gradient based methods. In this work, optimization problems pertaining to the vibration control of smart structures and the exploration of isospectral systems are addressed. Isospectral vibrating systems have identical natural frequencies, and existence of the isospectral systems proves non-uniqueness in system identification. For the smart structure problem, the optimal location(s) of collocated actuator(s)/sensor(s) and the optimal feedback gain matrix are obtained by maximizing the energy dissipated by the feedback control system. For the isospectral system problem, both discrete and continuous systems are considered. An error function is designed to calculate the error between the spectra of two distinct structural dynamic systems. For the discrete system, the Jacobi matrix, derived from the given system, is modified and the problem is posed as an optimization problem where the objective is to minimize the non-negative error function. Isospectral spring-mass systems are obtained. For the continuous system, finite element modeling is used and an error function is designed to calculate the error between the spectra of the uniform beam and the non-uniform beam. Non-uniform cantilever beams which are isospectral to a given uniform cantilever beam are obtained by minimizing the non-negative error function. Numerical studies reveal several isospectral systems, and optimal gain matrices and sensor/actuator locations for the smart structure. New evolutionary algorithms, which do not need genetic operators such as crossover and mutation, are used for the optimization. These algorithms are: Artificial bee colony (ABC) algorithm, Glowworm swarm optimization (GSO) algorithm, Firefly algorithm (FA) and Electromagnetism inspired optimization (EIO) algorithm.