This thesis presents short DNA alignment tools optimization. These short DNA reads are products of next\nobreakdash-generation sequencing technologies. The results produced by existing align\-ment tools can be influenced by various parameters. For this purpose, an optimization framework to find the optimal values of selected parameters was developed. This framework is based on differencial evolution algorithm and its main goal is to maximize the alignment accuracy. The functionality of the framework was tested on both real and generated data sets of short DNA reads. An accurate alignment is crucial for correct prediction of various genetic characteristics.

The modern industry is steadily facing new demands for more energy efficient solutions. These improvements can come from technological advances, using existing technology smarter or a combination of the two. Today a vacuum conveying system is manually tuned for each factory application when installed and is in most cases not handled afterwards except for maintenance reasons. This in combination with the difficulties in tuning a system to run efficiently and robustly whilst offering high capacity indicates that a large number of systems are running with non optimal settings. The aim of this thesis was therefore to explore the possibility of introducing an auto tuning property to the vacuum conveying system and investigate the possible benefits. This thesis has investigated two main components for such an autotuner, the system design and optimisation strategy. The system design is critical for allowing process control and monitoring. In the optimisation the main challenge was to robustly produce good results for a wide variety of materials. Based on this a laboratory system was developed that monitored the capacity, efficiency, gentleness and robustness performance of the conveying. This information was then used in anevolutionary optimisation algorithm based on differential evolution to find the best settings for optimal performance. The results of this thesis indicate that such a system would offer benefits bothin terms of initial tuning and run-time performance. The suggested auto tuner is adaptable to a large set of materials with varying material properties and demands on the conveying process. The time required for the laboratory rig to optimise within a region with only small deviations in performance is comparable to that of a human operator. Also with the added benefit of never having to stop the optimisation process, thus constantly improving performance and counteracting environmental changes. / Den moderna industrin möter ständigt nya krav på ökad effektivitet. Dessa förbättringar kan komma utifrån tillämpning av ny teknologi eller bättre utnyttjande av befintlig teknologi eller en kombination. Idag när en vakuum transportör installeras finjusteras den manuellt för att uppnå önskad prestanda och hanteras därefter ofta inte bortsett från underhållsarbete. Detta i kombination med svårigheten att justera ett system så att det går effektivt och robust samtidigt som en god kapacitet upprätthålls föranleder slutsatsen att många system ute i industrin inte presterar optimalt. Målet med detta examensarbete var därför att utreda möjligheten att skapa en automatisk system inställare samt utvärdera de möjliga fördelarna och nackdelarna. Arbetet har undersökt två huvudkomponenter i en sådan automatisk system inställare, system design och optimerings strategi. System design var vital för att tillåta styrning och monitorering av systemet och optimeringsstrategi för att tillförlitligt kunna prestera goda resultat trots skiftande beteende med olika material i systemet. Baserat på detta utvecklades en laboratorie-utrustning som övervakade kapacitet, effektivitet, robusthet och försiktighet i varje transportcykel. Denna information nyttjades sedan i en evolutionär algoritm baserad på differentierad evolution för att finna de optimala system-inställningarna. Arbetet indikerar att ett sådant system skulle erbjuda prestanda-fördelar både i driftsättande och kontinuerliga driften av en vakuum-transportör. Den föreslagna automatiska systeminställaren kan anpassas till en stor mängd material och skilda krav på önskat driftläge för systemet. Tiden för att optimera systemet så att de större variationerna i prestanda uppnås är jämförbar med en mänsklig operatör menkan fortlöpa över tiden och ständigt söka förbättringar på ett sätt som ej är möjligt för en mänsklig operatör.

No / A membrane-inspired evolutionary algorithm (MIEA) is a successful instance of a model linking membrane computing and evolutionary algorithms. This paper proposes the analysis of dynamic behaviors of MIEAs by introducing a set of population diversity and convergence measures. This is the first attempt to obtain additional insights into the search capabilities of MIEAs. The analysis is performed on the MIEA, QEPS (a quantum-inspired evolutionary algorithm based on membrane computing), and its counterpart algorithm, QIEA (a quantum-inspired evolutionary algorithm), using a comparative approach in an experimental context to better understand their characteristics and performances. Also the relationship between these measures and fitness is analyzed by presenting a tendency correlation coefficient to evaluate the importance of various population and convergence measures, which is beneficial to further improvements of MIEAs. Results show that QEPS can achieve better balance between convergence and diversity than QIEA, which indicates QEPS has a stronger capacity of balancing exploration and exploitation than QIEA in order to prevent premature convergence that might occur. Experiments utilizing knapsack problems support the above made statement.

No / This paper proposes an approximate optimization approach, called QEAM, which combines a P system with active membranes and a quantum-inspired evolutionary algorithm. QEAM uses the hierarchical arrangement of the compartments and developmental rules of a P system with active membranes, and the objects consisting of quantum-inspired bit individuals, a probabilistic observation and the evolutionary rules designed with quantum-inspired gates to specify the membrane algorithms. A large number of experiments carried out on benchmark instances of satisfiability problem show that QEAM outperforms QEPS (quantum-inspired evolutionary algorithm based on P systems) and its counterpart quantum-inspired evolutionary algorithm.

La prise de décision est une partie intégrante de notre vie quotidienne où le décideur est confronté à des problèmes composés de plusieurs objectifs habituellement contradictoires. Dans ce travail, nous traitons des problèmes d'optimisation multiobjectif dans des espaces de recherche continus ou discrets. Nous avons développé plusieurs nouveaux algorithmes basés sur les métaheuristiques hybrides évolutionnaires, en particulier sur l'algorithme MOEA/D. Nous avons proposé l'algorithme HEMH qui utilise l'algorithme DM-GRASP pour construire une population initiale de solutions de bonne qualité dispersées le long de l'ensemble des solutions Pareto optimales. Les résultats expérimentaux montrent la supériorité de toutes les variantes hybrides proposées sur les algorithmes originaux MOEA/D et SPEA2. Malgré ces bons résultats, notre approche possède quelques limitations, levées dans une version améliorée de HEMH : HEMH2 et deux autres variantes HEMHde et HEMHpr. Le Adaptive Binary DE inclus dans les HEMH2 et HEMHde a de meilleures capacités d'exploration qui pallient aux capacités de recherche locale contenues dans la HEMH, HEMH2 et HEMHde. Motivés par ces résultats, nous avons proposé un nouvel algorithme baptisé HESSA pour explorer un espace continu de recherche où le processus de recherche est réalisé par différentes stratégies de recherche. Les résultats expérimentaux montrent la supériorité de HESSA à la fois sur MOEA/D et dMOPSO. Tous les algorithmes proposés ont été vérifiés, testé et comparés à certaines méthodes MOEAs. Les résultats expérimentaux montrent que toutes les propositions sont très compétitives et peuvent être considérés comme une alternative fiable / Many real-world decision making problems consist of several conflicting objectives, the solutions of which is called the Pareto-optimal set. Hybrid metaheuristics proved their efficiency in solving these problems. They tend to enhance search capabilities by incorporating different metaheuristics. Thus, we are concerned with developing new hybrid schemes by incorporating different strategies with exploiting the pros and avoiding the drawback of the original ones. First, HEMH is proposed in which the search process includes two phases DMGRASP obtains an initial set of efficient solutions in the 1st phase. Then, greedy randomized path-relinking with local search or reproduction operators explore the non-visited regions. The efficient solutions explored over the search are collected. Second, a comparative study is developed to study the hybridization of different metaheuristics with MOEA/D. The 1st proposal combines adaptive discrete differential Evolution with MOEA/D. The 2nd combines greedy path-relinking with MOEA/D. The 3rd and the 4th proposals combine both of them in MOEA/D. Third, an improved version of HEMH is presented. HEMH2 uses inverse greedy to build its initial population. Then, differential evolution and path-relink improves these solutions by investigating the non-visited regions in the search space. Also, Pareto adaptive epsilon concept controls the archiving process. Motivated by the obtained results, HESSA is proposed to solve continuous problems. It adopts a pool of search strategies, each of which has a specified success ratio. A new offspring is generated using a randomly selected one. Then, the success ratios are adapted according to the success of the generated offspring. The efficient solutions are collected to act as global guides. The proposed algorithms are verified against the state of the art MOEAs using a set of instances from literature. Results indicate that all proposals are competitive and represent viable alternatives

Evolutionary algorithms belongs among the youngest and the most progressive methods of solving difficult optimization tasks. They received huge popularity mainly due to good experimental results in optimization, a simplicity of the implementation and a high modularity, which is an ability to be modified for different problems. Among the most frequently used Evolutionary algorithms belongs Genetic Algorithm, Differential Evolution and Evolutionary Strategy. It is able to apply these algorithms and theirs variants to both continuous, discrete and mixed optimization tasks. A subject of this theses is to compare three main types of algorithms on the catalyst optimization task with mixed variables, linear constraints and experimentally evaluated fitness function.

Cette thèse s’intéresse à l’étude d’une structure de moteur électrique à aimants permanents afin de réduire l’utilisation d’aimants à basse de terres rares et qui puisse être utilisée pour des applications industrielles. Il est montré dans la première partie de ce travail de recherche que la machine synchro-réluctante à aimants permanents est une bonne solution potentielle. Une analyse paramétrique est alors réalisée en utilisant une modélisation par éléments finis pour mettre en évidence les particularités de son comportement électromagnétique. Puis, une modélisation analytique multi-physique innovante du système convertisseur-moteur est détaillée dans le but de calculer les performances de ce dernier en un temps raisonnable. Les modèles multi-physiques présentés dans ces travaux concernent l’onduleur et le moteur. Ils intègrent les aspects électromagnétique, électrique, énergétique, thermique, mécanique et technico-économique. Le modèle multi-physique de la machine électrique est validé par comparaison à des résultats d’essais sur un prototype. Le modèle du système qui a été développé est ensuite utilisé dans une procédure de conception par optimisation de systèmes d’entrainements. Pour cela, une démarche d’optimisation originale est présentée pour le dimensionnement conjoint de deux applications en imposant la contrainte d’utiliser la même tôlerie magnétique. Il s’agit d’une part d’une application à vitesse fixe et d’autre part d’une application de type traction électrique. La méthode d’optimisation employée est à évolution différentielle. Les résultats des optimisations réalisées permettent de déterminer des conceptions optimales ou des compromis optimaux aux sens de Pareto qui répondent aux deux applications visées. Finalement, cette thèse a permis de positionner la machine synchro-réluctante à aimants permanents parmi les structures de machines à fort potentiel industriel. / This thesis focuses on the study of a structure of permanent magnet electric motor which reduces the amount used of permanent magnets composed of rare earths and which can be used in industrial applications. In the first part of the research work, it is shown that the permanent magnet assisted synchronous reluctance machine is a good alternative. A parametric analyse is realised using a finite element modelling in order to highlight the peculiarities of its electromagnetic behaviour. Then, an innovative multi-physic analytical modelling for the system inverter-motor is detailed in order to evaluate its performances in a reasonable computational time. The multi-physic models presented in this work concern the inverter and motor. They integrate the electromagnetic, electric, energetic, thermal, mechanic, and techno-economic aspects. The multi-physical model of the electric machine is validated by means of tests carried out on a prototype. The model of the system which has been developed is used in a design procedure by optimization of drive systems. For this purpose, an original optimization approach is presented for the simultaneous design of two applications by imposing the constraint of using the same magnetic lamination. On one hand it is an application of fixed speed and on the other hand an application of electric traction. The optimization method used is a type of differential evolution optimization. The results of the optimizations realised determine the optimal designs or the optimal compromise with Pareto front which deal with both applications. Finally, this thesis has placed the permanent magnet assisted synchronous reluctance machine among structures of machines with great industrial potential.

Cette thèse s’intéresse à l’étude d’une structure de moteur électrique à aimants permanents afin de réduire l’utilisation d’aimants à basse de terres rares et qui puisse être utilisée pour des applications industrielles. Il est montré dans la première partie de ce travail de recherche que la machine synchro-réluctante à aimants permanents est une bonne solution potentielle. Une analyse paramétrique est alors réalisée en utilisant une modélisation par éléments finis pour mettre en évidence les particularités de son comportement électromagnétique. Puis, une modélisation analytique multi-physique innovante du système convertisseur-moteur est détaillée dans le but de calculer les performances de ce dernier en un temps raisonnable. Les modèles multi-physiques présentés dans ces travaux concernent l’onduleur et le moteur. Ils intègrent les aspects électromagnétique, électrique, énergétique, thermique, mécanique et technico-économique. Le modèle multi-physique de la machine électrique est validé par comparaison à des résultats d’essais sur un prototype. Le modèle du système qui a été développé est ensuite utilisé dans une procédure de conception par optimisation de systèmes d’entrainements. Pour cela, une démarche d’optimisation originale est présentée pour le dimensionnement conjoint de deux applications en imposant la contrainte d’utiliser la même tôlerie magnétique. Il s’agit d’une part d’une application à vitesse fixe et d’autre part d’une application de type traction électrique. La méthode d’optimisation employée est à évolution différentielle. Les résultats des optimisations réalisées permettent de déterminer des conceptions optimales ou des compromis optimaux aux sens de Pareto qui répondent aux deux applications visées. Finalement, cette thèse a permis de positionner la machine synchro-réluctante à aimants permanents parmi les structures de machines à fort potentiel industriel. / This thesis focuses on the study of a structure of permanent magnet electric motor which reduces the amount used of permanent magnets composed of rare earths and which can be used in industrial applications. In the first part of the research work, it is shown that the permanent magnet assisted synchronous reluctance machine is a good alternative. A parametric analyse is realised using a finite element modelling in order to highlight the peculiarities of its electromagnetic behaviour. Then, an innovative multi-physic analytical modelling for the system inverter-motor is detailed in order to evaluate its performances in a reasonable computational time. The multi-physic models presented in this work concern the inverter and motor. They integrate the electromagnetic, electric, energetic, thermal, mechanic, and techno-economic aspects. The multi-physical model of the electric machine is validated by means of tests carried out on a prototype. The model of the system which has been developed is used in a design procedure by optimization of drive systems. For this purpose, an original optimization approach is presented for the simultaneous design of two applications by imposing the constraint of using the same magnetic lamination. On one hand it is an application of fixed speed and on the other hand an application of electric traction. The optimization method used is a type of differential evolution optimization. The results of the optimizations realised determine the optimal designs or the optimal compromise with Pareto front which deal with both applications. Finally, this thesis has placed the permanent magnet assisted synchronous reluctance machine among structures of machines with great industrial potential.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Um Estudo para a solução numérica do modelo de difusão com retenção, proposta por Bevilacqua et al. (2011), é apresentado, bem como uma formulação implícita para o problema inverso para a estimativa dos parâmetros envolvidos na formulação matemática do modelo. Através de um estudo minucioso da análise de sensibilidade e do cálculo do coeficiente de correlação de Pearson, são identificadas as chances de se obter sucesso na solução do problema inverso através do método determinístico de Levenberg-Marquardt e dos métodos estocásticos Algoritmo de Colisão de Partículas (Particle Collision Algorithm - PCA) e Evolução Diferencial (Differential Evolution - DE). São apresentados os resultados obtidos através destes três métodos de otimização para três casos de conjunto de parâmetros. Foi observada uma forte correlação entre dois destes três parâmetros, o que dificultou a estimativa simultânea dos mesmos. Porém, foi obtido sucesso nas estimativas individuais de cada parâmetro. Foram obtidos bons resultados para os fatores que multiplicam os termos diferenciais da equação que modela o fenômeno de difusão com retenção. / A Study for the numerical solution of the diffusion model with retention, proposed by Bevilacqua et al.(2011), using the finite difference method is presented, as well as an implicit formulation for the inverse problem to estimate the parameters involved in the formulation of the mathematical model. Through of a thorougth study of sensitivity analysis and calculating the Pearson correlation coefficient, are identified the chances of success in solving the inverse problem using the deterministic method of Levenberg-Marquardt and stochastic methods Particle Collision Algorithm - PCA and Differential Evolution - DE. Presents the results obtained from these three methods of optimization for three cases of parameter set. We observed a strong correlation between two of these three parameters, making it difficult to estimate simultaneously the same. However, success was obtained in the individual estimates for each parameter. Good results were obtained for the factors that increase the terms of the differential equation that models the phenomenon of diffusion with retention.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Sistemas estruturais em suas variadas aplicações incluindo-se veículos espaciais, automóveis e estruturas de engenharia civil tais como prédios, pontes e plataformas off-shore, acumulam dano durante suas vidas úteis. Em muitas situações, tal dano pode não ser visualmente observado. Do ponto de vista da segurança e da performance da estrutura, é desejável monitorar esta possível ocorrência, localizá-la e quantificá-la. Métodos de identificação de sistemas, que em geral, são classificados numa categoria de Técnicas de Avaliação Não-Destrutivas, podem ser utilizados para esta finalidade. Usando dados experimentais tais como frequências naturais, modos de vibração e deslocamentos estáticos, e um modelo analítico estrutural, parâmetros da estrutura podem ser identificados. As propriedades estruturais do modelo analítico são modificadas de modo a minimizar a diferença entre os dados obtidos por aquele modelo e a resposta medida. Isto pode ser definido como um problema inverso onde os parâmetros da estrutura são identificados. O problema inverso, descrito acima, foi resolvido usando métodos globais de otimização devido à provável presença de inúmeros mínimos locais e a não convexidade do espaço de projeto. Neste trabalho o método da Evolução Diferencial (Differential Evolution, DE) foi utilizado como ferramenta principal de otimização. Trata-se de uma meta-heurística inspirada numa população de soluções sucessivamente atualizada por operações aritméticas como mutações, recombinações e critérios de seleção dos melhores indivíduos até que um critério de convergência seja alcançado. O método da Evolução Diferencial foi desenvolvido como uma heurística para minimizar funções não diferenciáveis e foi aplicado a estruturas planas de treliças com diferentes níveis de danos. / Structural systems in a variety of applications including aerospace vehicles, automobiles and civil engineering structures such as tall buildings, bridges and offshore platforms, accumulate damage during their service life. In several situations, such damage may not be visually observable. From the standpoint of both safety and performance, it is desirable to monitor the occurrence, location and extent of such damage.System identification methods, which may be classified in a general category of nondestructive evaluation techniques, can be employed for this purpose. Using experimental data, such as eigenmodes, eigenvectors and static displacements, and an analytical structural model, parameters of the structures can be identified. The approach used in the present work is one where the structural properties of the analytical model are varied to minimize the difference between the analytically predicted and empirically measured response. This is an inverse problem where the structural parameters are identified. In this work a reduced number of vibration modes were used as the measured response. For the damage assessment problem a close analytical model of the structural system is available and the model of the damaged structure will be identified. Damage will be represented by a reduction in the elastic stiffness properties of the structure.The problem described above was solved using global methods of optimization due to the fact that depending on the number of variables or the location of damage the resulting design space is nonconvex presenting several local minima. In the present work, the Differential Evolution Optimization Technique (DE) was used. It is a metaheuristic inspired by a population of solutions that is successively updated by arithmetic operations such as mutation and recombination, until convergence. The approach was applied to simple truss structures with different levels of damage.