Regularized model learning in EDAs for continuous and multi-objective optimization

Probabilistic modeling is the de�ning characteristic of estimation of distribution algorithms (EDAs) which determines their behavior and performance in optimization. Regularization is a well-known statistical technique used for obtaining an improved model by reducing the generalization error of estimation, especially in high-dimensional problems. `1-regularization is a type of this technique with the appealing variable selection property which results in sparse model estimations. In this thesis, we study the use of regularization techniques for model learning in EDAs. Several methods for regularized model estimation in continuous domains based on a Gaussian distribution assumption are presented, and analyzed from di�erent aspects when used for optimization in a high-dimensional setting, where the population size of EDA has a logarithmic scale with respect to the number of variables. The optimization results obtained for a number of continuous problems with an increasing number of variables show that the proposed EDA based on regularized model estimation performs a more robust optimization, and is able to achieve signi�cantly better results for larger dimensions than other Gaussian-based EDAs. We also propose a method for learning a marginally factorized Gaussian Markov random �eld model using regularization techniques and a clustering algorithm. The experimental results show notable optimization performance on continuous additively decomposable problems when using this model estimation method. Our study also covers multi-objective optimization and we propose joint probabilistic modeling of variables and objectives in EDAs based on Bayesian networks, speci�cally models inspired from multi-dimensional Bayesian network classi�ers. It is shown that with this approach to modeling, two new types of relationships are encoded in the estimated models in addition to the variable relationships captured in other EDAs: objectivevariable and objective-objective relationships. An extensive experimental study shows the e�ectiveness of this approach for multi- and many-objective optimization. With the proposed joint variable-objective modeling, in addition to the Pareto set approximation, the algorithm is also able to obtain an estimation of the multi-objective problem structure. Finally, the study of multi-objective optimization based on joint probabilistic modeling is extended to noisy domains, where the noise in objective values is represented by intervals. A new version of the Pareto dominance relation for ordering the solutions in these problems, namely �-degree Pareto dominance, is introduced and its properties are analyzed. We show that the ranking methods based on this dominance relation can result in competitive performance of EDAs with respect to the quality of the approximated Pareto sets. This dominance relation is then used together with a method for joint probabilistic modeling based on `1-regularization for multi-objective feature subset selection in classi�cation, where six di�erent measures of accuracy are considered as objectives with interval values. The individual assessment of the proposed joint probabilistic modeling and solution ranking methods on datasets with small-medium dimensionality, when using two di�erent Bayesian classi�ers, shows that comparable or better Pareto sets of feature subsets are approximated in comparison to standard methods.

Metaheuristic approaches for MWT and MWPT problems

It is known that the Minimum Weight Triangulation problem is NP-hard. Also the complexity of the Minimum Weight Pseudo-Triangulation problem is unknown, yet it is suspected to be also NP-hard. Therefore we focused on the development of approximate algorithms to find high quality triangulations and pseudo-triangulations of minimum weight. In this work we propose two metaheuristics to solve these problems: Ant Colony Optimization (ACO) and Simulated Annealing (SA). For the experimental study we have created a set of instances for MWT and MWPT problems, since no reference to benchmarks for these problems were found in the literature. Through experimental evaluation, we assess the applicability of the ACO and SA metaheuristics for MWT and MWPT problems. These results are compared with those obtained from the application of deterministic algorithms for the same problems (Delaunay Triangulation for MWT and a Greedy algorithm respectively for MWT and MWPT).

Approximations on minimum weight pseudo-triangulation problem using ant colony optimization

In this work, we consider the Minimum Weight Pseudo-Triangulation (MWPT) problem of a given set of n points in the plane. Globally optimal pseudo-triangulations with respect to the weight, as optimization criteria, are difficult to be found by deterministic methods, since no polynomial algorithm is known. We show how the Ant Colony Optimization (ACO) metaheuristic can be used to find high quality pseudo-triangulations of minimum weight. We present the experimental and statistical study based on our own set of instances since no reference to benchmarks for these problems were found in the literature. Throughout the experimental evaluation, we appraise the ACO metaheuristic performance for MWPT problem.

Dynamic Response Optimization of Vehicles through Efficient Multibody Formulations and Automatic Differentiation Techniques

El diseño y desarrollo de sistemas de suspensión para vehículos se basa cada día más en el diseño por ordenador y en herramientas de análisis por ordenador, las cuales permiten anticipar problemas y resolverlos por adelantado. El comportamiento y las características dinámicas se calculan con precisión, bajo coste, y recursos y tiempos de cálculo reducidos. Sin embargo, existe una componente iterativa en el proceso, que requiere la definición manual de diseños a través de técnicas “prueba y error”. Esta Tesis da un paso hacia el desarrollo de un entorno de simulación eficiente capaz de simular, analizar y evaluar diseños de suspensiones vehiculares, y de mejorarlos hacia la solución optima mediante la modificación de los parámetros de diseño. La modelización mediante sistemas multicuerpo se utiliza aquí para desarrollar un modelo de autocar con 18 grados de libertad, de manera detallada y eficiente. La geometría y demás características de la suspensión se ajustan a las del vehículo real, así como los demás parámetros del modelo. Para simular la dinámica vehicular, se utiliza una formulación multicuerpo moderna y eficiente basada en las ecuaciones de Maggi, a la que se ha incorporado un visor 3D. Así, se consigue simular maniobras vehiculares en tiempos inferiores al tiempo real. Una vez que la dinámica está disponible, los análisis de sensibilidad son cruciales para una optimización robusta y eficiente. Para ello, se presenta una técnica matemática que permite derivar las variables dinámicas dentro de la formulación, de forma algorítmica, general, con la precisión de la maquina, y razonablemente eficiente: la diferenciación automática. Este método propaga las derivadas con respecto a las variables de diseño a través del código informático y con poca intervención del usuario. En contraste con otros enfoques en la bibliografía, generalmente particulares y limitados, se realiza una comparación de librerías, se desarrolla una formulación híbrida directa-automática para el cálculo de sensibilidades, y se presentan varios ejemplos reales. Finalmente, se lleva a cabo la optimización de la respuesta dinámica del vehículo citado. Se analizan cuatro tipos distintos de optimización: identificación de parámetros, optimización de la maniobrabilidad, optimización del confort y optimización multi-objetivo, todos ellos aplicados al diseño del autocar. Además de resultados analíticos y gráficos, se incluyen algunas consideraciones acerca de la eficiencia. En resumen, se mejora el comportamiento dinámico de vehículos por medio de modelos multicuerpo y de técnicas de diferenciación automática y optimización avanzadas, posibilitando un ajuste automático, preciso y eficiente de los parámetros de diseño. ABSTRACT Each day, the design and development of vehicle suspension systems relies more on computer-aided design and computer-aided engineering tools, which allow anticipating the problems and solving them ahead of time. Dynamic behavior and characteristics are thus simulated accurately and inexpensively with moderate computational times and resources. There is, however, an iterative component in the process, which involves the manual definition of designs in a trialand-error manner. This Thesis takes a step towards the development of an efficient simulation framework capable of simulating, analyzing and evaluating vehicle suspension designs, and automatically improving them by varying the design parameters towards the optimal solution. The multibody systems approach is hereby used to model a three-dimensional 18-degrees-of-freedom coach in a comprehensive yet efficient way. The suspension geometry and characteristics resemble the ones from the real vehicle, as do the rest of vehicle parameters. In order to simulate vehicle dynamics, an efficient, state-of-the-art multibody formulation based on Maggi’s equations is employed, and a three-dimensional graphics viewer is developed. As a result, vehicle maneuvers can be simulated faster than real-time. Once the dynamics are ready, a sensitivity analysis is crucial for a robust optimization. To that end, a mathematical technique is introduced, which allows differentiating the dynamic variables within the multibody formulation in a general, algorithmic, accurate to machine precision, and reasonably efficient way: automatic differentiation. This method propagates the derivatives with respect to the design parameters throughout the computer code, with little user interaction. In contrast with other attempts in the literature, mostly not generalpurpose, a benchmarking of libraries is carried out, a hybrid direct-automatic differentiation approach for the computation of sensitivities is developed, and several real-life examples are analyzed. Finally, a design optimization process of the aforementioned vehicle is carried out. Four different types of dynamic response optimization are presented: parameter identification, handling optimization, ride comfort optimization and multi-objective optimization; all of which are applied to the design of the coach example. Together with analytical and visual proof of the results, efficiency considerations are made. In summary, the dynamic behavior of vehicles is improved by using the multibody systems approach, along with advanced differentiation and optimization techniques, enabling an automatic, accurate and efficient tuning of design parameters.

Aerodynamic Optimization of the Nose Shape of a High-speed Train

La influencia de la aerodinámica en el diseño de los trenes de alta velocidad, unida a la necesidad de resolver nuevos problemas surgidos con el aumento de la velocidad de circulación y la reducción de peso del vehículo, hace evidente el interés de plantear un estudio de optimización que aborde tales puntos. En este contexto, se presenta en esta tesis la optimización aerodinámica del testero de un tren de alta velocidad, llevada a cabo mediante el uso de métodos de optimización avanzados. Entre estos métodos, se ha elegido aquí a los algoritmos genéticos y al método adjunto como las herramientas para llevar a cabo dicha optimización. La base conceptual, las características y la implementación de los mismos se detalla a lo largo de la tesis, permitiendo entender los motivos de su elección, y las consecuencias, en términos de ventajas y desventajas que cada uno de ellos implican. El uso de los algorimos genéticos implica a su vez la necesidad de una parametrización geométrica de los candidatos a óptimo y la generación de un modelo aproximado que complementa al método de optimización. Estos puntos se describen de modo particular en el primer bloque de la tesis, enfocada a la metodología seguida en este estudio. El segundo bloque se centra en la aplicación de los métodos a fin de optimizar el comportamiento aerodinámico del tren en distintos escenarios. Estos escenarios engloban los casos más comunes y también algunos de los más exigentes a los que hace frente un tren de alta velocidad: circulación en campo abierto con viento frontal o viento lateral, y entrada en túnel. Considerando el caso de viento frontal en campo abierto, los dos métodos han sido aplicados, permitiendo una comparación de las diferentes metodologías, así como el coste computacional asociado a cada uno, y la minimización de la resistencia aerodinámica conseguida en esa optimización. La posibilidad de evitar parametrizar la geometría y, por tanto, reducir el coste computacional del proceso de optimización es la característica más significativa de los métodos adjuntos, mientras que en el caso de los algoritmos genéticos se destaca la simplicidad y capacidad de encontrar un óptimo global en un espacio de diseño multi-modal o de resolver problemas multi-objetivo. El caso de viento lateral en campo abierto considera nuevamente los dos métoxi dos de optimización anteriores. La parametrización se ha simplificado en este estudio, lo que notablemente reduce el coste numérico de todo el estudio de optimización, a la vez que aún recoge las características geométricas más relevantes en un tren de alta velocidad. Este análisis ha permitido identificar y cuantificar la influencia de cada uno de los parámetros geométricos incluídos en la parametrización, y se ha observado que el diseño de la arista superior a barlovento es fundamental, siendo su influencia mayor que la longitud del testero o que la sección frontal del mismo. Finalmente, se ha considerado un escenario más a fin de validar estos métodos y su capacidad de encontrar un óptimo global. La entrada de un tren de alta velocidad en un túnel es uno de los casos más exigentes para un tren por el pico de sobrepresión generado, el cual afecta a la confortabilidad del pasajero, así como a la estabilidad del vehículo y al entorno próximo a la salida del túnel. Además de este problema, otro objetivo a minimizar es la resistencia aerodinámica, notablemente superior al caso de campo abierto. Este problema se resuelve usando algoritmos genéticos. Dicho método permite obtener un frente de Pareto donde se incluyen el conjunto de óptimos que minimizan ambos objetivos. ABSTRACT Aerodynamic design of trains influences several aspects of high-speed trains performance in a very significant level. In this situation, considering also that new aerodynamic problems have arisen due to the increase of the cruise speed and lightness of the vehicle, it is evident the necessity of proposing an optimization study concerning the train aerodynamics. Thus, the aerodynamic optimization of the nose shape of a high-speed train is presented in this thesis. This optimization is based on advanced optimization methods. Among these methods, genetic algorithms and the adjoint method have been selected. A theoretical description of their bases, the characteristics and the implementation of each method is detailed in this thesis. This introduction permits understanding the causes of their selection, and the advantages and drawbacks of their application. The genetic algorithms requirethe geometrical parameterization of any optimal candidate and the generation of a metamodel or surrogate model that complete the optimization process. These points are addressed with a special attention in the first block of the thesis, focused on the methodology considered in this study. The second block is referred to the use of these methods with the purpose of optimizing the aerodynamic performance of a high-speed train in several scenarios. These scenarios englobe the most representative operating conditions of high-speed trains, and also some of the most exigent train aerodynamic problems: front wind and cross-wind situations in open air, and the entrance of a high-speed train in a tunnel. The genetic algorithms and the adjoint method have been applied in the minimization of the aerodynamic drag on the train with front wind in open air. The comparison of these methods allows to evaluate the methdology and computational cost of each one, as well as the resulting minimization of the aerodynamic drag. Simplicity and robustness, the straightforward realization of a multi-objective optimization, and the capability of searching a global optimum are the main attributes of genetic algorithm. However, the requirement of geometrically parameterize any optimal candidate is a significant drawback that is avoided with the use of the adjoint method. This independence of the number of design variables leads to a relevant reduction of the pre-processing and computational cost. Considering the cross-wind stability, both methods are used again for the minimization of the side force. In this case, a simplification of the geometric parameterization of the train nose is adopted, what dramatically reduces the computational cost of the optimization process. Nevertheless, some of the most important geometrical characteristics are still described with this simplified parameterization. This analysis identifies and quantifies the influence of each design variable on the side force on the train. It is observed that the A-pillar roundness is the most demanding design parameter, with a more important effect than the nose length or the train cross-section area. Finally, a third scenario is considered for the validation of these methods in the aerodynamic optimization of a high-speed train. The entrance of a train in a tunnel is one of the most exigent train aerodynamic problems. The aerodynamic consequences of high-speed trains running in a tunnel are basically resumed in two correlated phenomena, the generation of pressure waves and an increase in aerodynamic drag. This multi-objective optimization problem is solved with genetic algorithms. The result is a Pareto front where a set of optimal solutions that minimize both objectives.

A multi-criteria optimization and decision-making approach for improvement of food engineering processes.

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demostrated using experimental data obtained on osmotic dehydratation of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

Business Process Optimization in Madrid City Council.

While designing systems and products requires a deep understanding of influences that achieve desirable performance, the need for an efficient and systematic decision-making approach drives the need for optimization strategies. This paper provides the motivation for this topic as well as a description of applications in Computing Center of Madrid city Council. Optimization applications can be found in almost all areas of engineering. Typical problems in process, working with a database, arise in query design, entity model design and concurrent processes. This paper proposes a solution to optimize a night process dealing with millions of records with an overall performance of about eight times in computation time.

A framework for the analysis and optimization of delay in multiview video coding schemes

Esta tesis presenta un novedoso marco de referencia para el análisis y optimización del retardo de codificación y descodificación para vídeo multivista. El objetivo de este marco de referencia es proporcionar una metodología sistemática para el análisis del retardo en codificadores y descodificadores multivista y herramientas útiles en el diseño de codificadores/descodificadores para aplicaciones con requisitos de bajo retardo. El marco de referencia propuesto caracteriza primero los elementos que tienen influencia en el comportamiento del retardo: i) la estructura de predicción multivista, ii) el modelo hardware del codificador/descodificador y iii) los tiempos de proceso de cuadro. En segundo lugar, proporciona algoritmos para el cálculo del retardo de codificación/ descodificación de cualquier estructura arbitraria de predicción multivista. El núcleo de este marco de referencia consiste en una metodología para el análisis del retardo de codificación/descodificación multivista que es independiente de la arquitectura hardware del codificador/descodificador, completada con un conjunto de modelos que particularizan este análisis del retardo con las características de la arquitectura hardware del codificador/descodificador. Entre estos modelos, aquellos basados en teoría de grafos adquieren especial relevancia debido a su capacidad de desacoplar la influencia de los diferentes elementos en el comportamiento del retardo en el codificador/ descodificador, mediante una abstracción de su capacidad de proceso. Para revelar las posibles aplicaciones de este marco de referencia, esta tesis presenta algunos ejemplos de su utilización en problemas de diseño que afectan a codificadores y descodificadores multivista. Este escenario de aplicación cubre los siguientes casos: estrategias para el diseño de estructuras de predicción que tengan en consideración requisitos de retardo además del comportamiento tasa-distorsión; diseño del número de procesadores y análisis de los requisitos de velocidad de proceso en codificadores/ descodificadores multivista dado un retardo objetivo; y el análisis comparativo del comportamiento del retardo en codificadores multivista con diferentes capacidades de proceso e implementaciones hardware. ABSTRACT This thesis presents a novel framework for the analysis and optimization of the encoding and decoding delay for multiview video. The objective of this framework is to provide a systematic methodology for the analysis of the delay in multiview encoders and decoders and useful tools in the design of multiview encoders/decoders for applications with low delay requirements. The proposed framework characterizes firstly the elements that have an influence in the delay performance: i) the multiview prediction structure ii) the hardware model of the encoder/decoder and iii) frame processing times. Secondly, it provides algorithms for the computation of the encoding/decoding delay of any arbitrary multiview prediction structure. The core of this framework consists in a methodology for the analysis of the multiview encoding/decoding delay that is independent of the hardware architecture of the encoder/decoder, which is completed with a set of models that particularize this delay analysis with the characteristics of the hardware architecture of the encoder/decoder. Among these models, the ones based in graph theory acquire special relevance due to their capacity to detach the influence of the different elements in the delay performance of the encoder/decoder, by means of an abstraction of its processing capacity. To reveal possible applications of this framework, this thesis presents some examples of its utilization in design problems that affect multiview encoders and decoders. This application scenario covers the following cases: strategies for the design of prediction structures that take into consideration delay requirements in addition to the rate-distortion performance; design of number of processors and analysis of processor speed requirements in multiview encoders/decoders given a target delay; and comparative analysis of the encoding delay performance of multiview encoders with different processing capabilities and hardware implementations.

Multi-objective Aerodynamic Optimization of High-speed Trains in Tunnels

A genetic algorithm (GA) is employed for the multi-objective shape optimization of the nose of a high-speed train. Aerodynamic problems observed at high speeds become still more relevant when traveling along a tunnel. The objective is to minimize both the aerodynamic drag and the amplitude of the pressure gradient of the compression wave when a train enters a tunnel. The main drawback of GA is the large number of evaluations need in the optimization process. Metamodels-based optimization is considered to overcome such problem. As a result, an explicit relationship between pressure gradient and geometrical parameters is obtained.

High Efficiency Envelope Amplifier based on a Ripple Cancellation Buck Converter. Design, Optimization and Integration in an EER RFPA

Durante los últimos años la tendencia en el sector de las telecomunicaciones ha sido un aumento y diversificación en la transmisión de voz, video y fundamentalmente de datos. Para conseguir alcanzar las tasas de transmisión requeridas, los nuevos estándares de comunicaciones requieren un mayor ancho de banda y tienen un mayor factor de pico, lo cual influye en el bajo rendimiento del amplificador de radiofrecuencia (RFPA). Otro factor que ha influido en el bajo rendimiento es el diseño del amplificador de radiofrecuencia. Tradicionalmente se han utilizado amplificadores lineales por su buen funcionamiento. Sin embargo, debido al elevado factor de pico de las señales transmitidas, el rendimiento de este tipo de amplificadores es bajo. El bajo rendimiento del sistema conlleva desventajas adicionales como el aumento del coste y del tamaño del sistema de refrigeración, como en el caso de una estación base, o como la reducción del tiempo de uso y un mayor calentamiento del equipo para sistemas portátiles alimentados con baterías. Debido a estos factores, se han desarrollado durante las últimas décadas varias soluciones para aumentar el rendimiento del RFPA como la técnica de Outphasing, combinadores de potencia o la técnica de Doherty. Estas soluciones mejoran las prestaciones del RFPA y en algún caso han sido ampliamente utilizados comercialmente como la técnica de Doherty, que alcanza rendimientos hasta del 50% para el sistema completo para anchos de banda de hasta 20MHz. Pese a las mejoras obtenidas con estas soluciones, los mayores rendimientos del sistema se obtienen para soluciones basadas en la modulación de la tensión de alimentación del amplificador de potencia como “Envelope Tracking” o “EER”. La técnica de seguimiento de envolvente o “Envelope Tracking” está basada en la modulación de la tensión de alimentación de un amplificador lineal de potencia para obtener una mejora en el rendimiento en el sistema comparado a una solución con una tensión de alimentación constante. Para la implementación de esta técnica se necesita una etapa adicional, el amplificador de envolvente, que añade complejidad al amplificador de radiofrecuencia. En un amplificador diseñado con esta técnica, se aumentan las pérdidas debido a la etapa adicional que supone el amplificador de envolvente pero a su vez disminuyen las pérdidas en el amplificador de potencia. Si el diseño se optimiza adecuadamente, puede conseguirse un aumento global en el rendimiento del sistema superior al conseguido con las técnicas mencionadas anteriormente. Esta técnica presenta ventajas en el diseño del amplificador de envolvente, ya que el ancho de banda requerido puede ser menor que el ancho de banda de la señal de envolvente si se optimiza adecuadamente el diseño. Adicionalmente, debido a que la sincronización entre la señal de envolvente y de fase no tiene que ser perfecta, el proceso de integración conlleva ciertas ventajas respecto a otras técnicas como EER. La técnica de eliminación y restauración de envolvente, llamada EER o técnica de Kahn está basada en modulación simultánea de la envolvente y la fase de la señal usando un amplificador de potencia conmutado, no lineal y que permite obtener un elevado rendimiento. Esta solución fue propuesta en el año 1952, pero no ha sido implementada con éxito durante muchos años debido a los exigentes requerimientos en cuanto a la sincronización entre fase y envolvente, a las técnicas de control y de corrección de los errores y no linealidades de cada una de las etapas así como de los equipos para poder implementar estas técnicas, que tienen unos requerimientos exigentes en capacidad de cálculo y procesamiento. Dentro del diseño de un RFPA, el amplificador de envolvente tiene una gran importancia debido a su influencia en el rendimiento y ancho de banda del sistema completo. Adicionalmente, la linealidad y la calidad de la señal de transmitida deben ser elevados para poder cumplir con los diferentes estándares de telecomunicaciones. Esta tesis se centra en el amplificador de envolvente y el objetivo principal es el desarrollo de soluciones que permitan el aumento del rendimiento total del sistema a la vez que satisfagan los requerimientos de ancho de banda, calidad de la señal transmitida y de linealidad. Debido al elevado rendimiento que potencialmente puede alcanzarse con la técnica de EER, esta técnica ha sido objeto de análisis y en el estado del arte pueden encontrarse numerosas referencias que analizan el diseño y proponen diversas implementaciones. En una clasificación de alto nivel, podemos agrupar las soluciones propuestas del amplificador de envolvente según estén compuestas de una o múltiples etapas. Las soluciones para el amplificador de envolvente en una configuración multietapa se basan en la combinación de un convertidor conmutado, de elevado rendimiento con un regulador lineal, de alto ancho de banda, en una combinación serie o paralelo. Estas soluciones, debido a la combinación de las características de ambas etapas, proporcionan un buen compromiso entre rendimiento y buen funcionamiento del amplificador de RF. Por otro lado, la complejidad del sistema aumenta debido al mayor número de componentes y de señales de control necesarias y el aumento de rendimiento que se consigue con estas soluciones es limitado. Una configuración en una etapa tiene las ventajas de una mayor simplicidad, pero debido al elevado ancho de banda necesario, la frecuencia de conmutación debe aumentarse en gran medida. Esto implicará un bajo rendimiento y un peor funcionamiento del amplificador de envolvente. En el estado del arte pueden encontrarse diversas soluciones para un amplificador de envolvente en una etapa, como aumentar la frecuencia de conmutación y realizar la implementación en un circuito integrado, que tendrá mejor funcionamiento a altas frecuencias o utilizar técnicas topológicas y/o filtros de orden elevado, que permiten una reducción de la frecuencia de conmutación. En esta tesis se propone de manera original el uso de la técnica de cancelación de rizado, aplicado al convertidor reductor síncrono, para reducir la frecuencia de conmutación comparado con diseño equivalente del convertidor reductor convencional. Adicionalmente se han desarrollado dos variantes topológicas basadas en esta solución para aumentar la robustez y las prestaciones de la misma. Otro punto de interés en el diseño de un RFPA es la dificultad de poder estimar la influencia de los parámetros de diseño del amplificador de envolvente en el amplificador final integrado. En esta tesis se ha abordado este problema y se ha desarrollado una herramienta de diseño que permite obtener las principales figuras de mérito del amplificador integrado para la técnica de EER a partir del diseño del amplificador de envolvente. Mediante el uso de esta herramienta pueden validarse el efecto del ancho de banda, el rizado de tensión de salida o las no linealidades del diseño del amplificador de envolvente para varias modulaciones digitales. Las principales contribuciones originales de esta tesis son las siguientes: La aplicación de la técnica de cancelación de rizado a un convertidor reductor síncrono para un amplificador de envolvente de alto rendimiento para un RFPA linealizado mediante la técnica de EER. Una reducción del 66% en la frecuencia de conmutación, comparado con el reductor convencional equivalente. Esta reducción se ha validado experimentalmente obteniéndose una mejora en el rendimiento de entre el 12.4% y el 16% para las especificaciones de este trabajo. La topología y el diseño del convertidor reductor con dos redes de cancelación de rizado en cascada para mejorar el funcionamiento y robustez de la solución con una red de cancelación. La combinación de un convertidor redactor multifase con la técnica de cancelación de rizado para obtener una topología que proporciona una reducción del cociente entre frecuencia de conmutación y ancho de banda de la señal. El proceso de optimización del control del amplificador de envolvente en lazo cerrado para mejorar el funcionamiento respecto a la solución en lazo abierto del convertidor reductor con red de cancelación de rizado. Una herramienta de simulación para optimizar el proceso de diseño del amplificador de envolvente mediante la estimación de las figuras de mérito del RFPA, implementado mediante EER, basada en el diseño del amplificador de envolvente. La integración y caracterización del amplificador de envolvente basado en un convertidor reductor con red de cancelación de rizado en el transmisor de radiofrecuencia completo consiguiendo un elevado rendimiento, entre 57% y 70.6% para potencias de salida de 14.4W y 40.7W respectivamente. Esta tesis se divide en seis capítulos. El primer capítulo aborda la introducción enfocada en la aplicación, los amplificadores de potencia de radiofrecuencia, así como los principales problemas, retos y soluciones existentes. En el capítulo dos se desarrolla el estado del arte de amplificadores de potencia de RF, describiéndose las principales técnicas de diseño, las causas de no linealidad y las técnicas de optimización. El capítulo tres está centrado en las soluciones propuestas para el amplificador de envolvente. El modo de control se ha abordado en este capítulo y se ha presentado una optimización del diseño en lazo cerrado para el convertidor reductor convencional y para el convertidor reductor con red de cancelación de rizado. El capítulo cuatro se centra en el proceso de diseño del amplificador de envolvente. Se ha desarrollado una herramienta de diseño para evaluar la influencia del amplificador de envolvente en las figuras de mérito del RFPA. En el capítulo cinco se presenta el proceso de integración realizado y las pruebas realizadas para las diversas modulaciones, así como la completa caracterización y análisis del amplificador de RF. El capítulo seis describe las principales conclusiones de la tesis y las líneas futuras. ABSTRACT The trend in the telecommunications sector during the last years follow a high increase in the transmission rate of voice, video and mainly in data. To achieve the required levels of data rates, the new modulation standards demand higher bandwidths and have a higher peak to average power ratio (PAPR). These specifications have a direct impact in the low efficiency of the RFPA. An additional factor for the low efficiency of the RFPA is in the power amplifier design. Traditionally, linear classes have been used for the implementation of the power amplifier as they comply with the technical requirements. However, they have a low efficiency, especially in the operating range of signals with a high PAPR. The low efficiency of the transmitter has additional disadvantages as an increase in the cost and size as the cooling system needs to be increased for a base station and a temperature increase and a lower use time for portable devices. Several solutions have been proposed in the state of the art to improve the efficiency of the transmitter as Outphasing, power combiners or Doherty technique. However, the highest potential of efficiency improvement can be obtained using a modulated power supply for the power amplifier, as in the Envelope Tracking and EER techniques. The Envelope Tracking technique is based on the modulation of the power supply of a linear power amplifier to improve the overall efficiency compared to a fixed voltage supply. In the implementation of this technique an additional stage is needed, the envelope amplifier, that will increase the complexity of the RFPA. However, the efficiency of the linear power amplifier will increase and, if designed properly, the RFPA efficiency will be improved. The advantages of this technique are that the envelope amplifier design does not require such a high bandwidth as the envelope signal and that in the integration process a perfect synchronization between envelope and phase is not required. The Envelope Elimination and Restoration (EER) technique, known also as Kahn’s technique, is based on the simultaneous modulation of envelope and phase using a high efficiency switched power amplifier. This solution has the highest potential in terms of the efficiency improvement but also has the most challenging specifications. This solution, proposed in 1952, has not been successfully implemented until the last two decades due to the high demanding requirements for each of the stages as well as for the highly demanding processing and computation capabilities needed. At the system level, a very precise synchronization is required between the envelope and phase paths to avoid a linearity decrease of the system. Several techniques are used to compensate the non-linear effects in amplitude and phase and to improve the rejection of the out of band noise as predistortion, feedback and feed-forward. In order to obtain a high bandwidth and efficient RFPA using either ET or EER, the envelope amplifier stage will have a critical importance. The requirements for this stage are very demanding in terms of bandwidth, linearity and quality of the transmitted signal. Additionally the efficiency should be as high as possible, as the envelope amplifier has a direct impact in the efficiency of the overall system. This thesis is focused on the envelope amplifier stage and the main objective will be the development of high efficiency envelope amplifier solutions that comply with the requirements of the RFPA application. The design and optimization of an envelope amplifier for a RFPA application is a highly referenced research topic, and many solutions that address the envelope amplifier and the RFPA design and optimization can be found in the state of the art. From a high level classification, multiple and single stage envelope amplifiers can be identified. Envelope amplifiers for EER based on multiple stage architecture combine a linear assisted stage and a switched-mode stage, either in a series or parallel configuration, to achieve a very high performance RFPA. However, the complexity of the system increases and the efficiency improvement is limited. A single-stage envelope amplifier has the advantage of a lower complexity but in order to achieve the required bandwidth the switching frequency has to be highly increased, and therefore the performance and the efficiency are degraded. Several techniques are used to overcome this limitation, as the design of integrated circuits that are capable of switching at very high rates or the use of topological solutions, high order filters or a combination of both to reduce the switching frequency requirements. In this thesis it is originally proposed the use of the ripple cancellation technique, applied to a synchronous buck converter, to reduce the switching frequency requirements compared to a conventional buck converter for an envelope amplifier application. Three original proposals for the envelope amplifier stage, based on the ripple cancellation technique, are presented and one of the solutions has been experimentally validated and integrated in the complete amplifier, showing a high total efficiency increase compared to other solutions of the state of the art. Additionally, the proposed envelope amplifier has been integrated in the complete RFPA achieving a high total efficiency. The design process optimization has also been analyzed in this thesis. Due to the different figures of merit between the envelope amplifier and the complete RFPA it is very difficult to obtain an optimized design for the envelope amplifier. To reduce the design uncertainties, a design tool has been developed to provide an estimation of the RFPA figures of merit based on the design of the envelope amplifier. The main contributions of this thesis are: The application of the ripple cancellation technique to a synchronous buck converter for an envelope amplifier application to achieve a high efficiency and high bandwidth EER RFPA. A 66% reduction of the switching frequency, validated experimentally, compared to the equivalent conventional buck converter. This reduction has been reflected in an improvement in the efficiency between 12.4% and 16%, validated for the specifications of this work. The synchronous buck converter with two cascaded ripple cancellation networks (RCNs) topology and design to improve the robustness and the performance of the envelope amplifier. The combination of a phase-shifted multi-phase buck converter with the ripple cancellation technique to improve the envelope amplifier switching frequency to signal bandwidth ratio. The optimization of the control loop of an envelope amplifier to improve the performance of the open loop design for the conventional and ripple cancellation buck converter. A simulation tool to optimize the envelope amplifier design process. Using the envelope amplifier design as the input data, the main figures of merit of the complete RFPA for an EER application are obtained for several digital modulations. The successful integration of the envelope amplifier based on a RCN buck converter in the complete RFPA obtaining a high efficiency integrated amplifier. The efficiency obtained is between 57% and 70.6% for an output power of 14.4W and 40.7W respectively. The main figures of merit for the different modulations have been characterized and analyzed. This thesis is organized in six chapters. In Chapter 1 is provided an introduction of the RFPA application, where the main problems, challenges and solutions are described. In Chapter 2 the technical background for radiofrequency power amplifiers (RF) is presented. The main techniques to implement an RFPA are described and analyzed. The state of the art techniques to improve performance of the RFPA are identified as well as the main sources of no-linearities for the RFPA. Chapter 3 is focused on the envelope amplifier stage. The three different solutions proposed originally in this thesis for the envelope amplifier are presented and analyzed. The control stage design is analyzed and an optimization is proposed both for the conventional and the RCN buck converter. Chapter 4 is focused in the design and optimization process of the envelope amplifier and a design tool to evaluate the envelope amplifier design impact in the RFPA is presented. Chapter 5 shows the integration process of the complete amplifier. Chapter 6 addresses the main conclusions of the thesis and the future work.

A 3D multi-objective optimization planning algorithm for wireless sensor networks

The complexity of planning a wireless sensor network is dependent on the aspects of optimization and on the application requirements. Even though Murphy's Law is applied everywhere in reality, a good planning algorithm will assist the designers to be aware of the short plates of their design and to improve them before the problems being exposed at the real deployment. A 3D multi-objective planning algorithm is proposed in this paper to provide solutions on the locations of nodes and their properties. It employs a developed ray-tracing scheme for sensing signal and radio propagation modelling. Therefore it is sensitive to the obstacles and makes the models of sensing coverage and link quality more practical compared with other heuristics that use ideal unit-disk models. The proposed algorithm aims at reaching an overall optimization on hardware cost, coverage, link quality and lifetime. Thus each of those metrics are modelled and normalized to compose a desirability function. Evolutionary algorithm is designed to efficiently tackle this NP-hard multi-objective optimization problem. The proposed algorithm is applicable for both indoor and outdoor 3D scenarios. Different parameters that affect the performance are analyzed through extensive experiments; two state-of-the-art algorithms are rebuilt and tested with the same configuration as that of the proposed algorithm. The results indicate that the proposed algorithm converges efficiently within 600 iterations and performs better than the compared heuristics.

Two-dimensional mesh optimization in the finite element method

The solution to the problem of finding the optimum mesh design in the finite element method with the restriction of a given number of degrees of freedom, is an interesting problem, particularly in the applications method. At present, the usual procedures introduce new degrees of freedom (remeshing) in a given mesh in order to obtain a more adequate one, from the point of view of the calculation results (errors uniformity). However, from the solution of the optimum mesh problem with a specific number of degrees of freedom some useful recommendations and criteria for the mesh construction may be drawn. For 1-D problems, namely for the simple truss and beam elements, analytical solutions have been found and they are given in this paper. For the more complex 2-D problems (plane stress and plane strain) numerical methods to obtain the optimum mesh, based on optimization procedures have to be used. The objective function, used in the minimization process, has been the total potential energy. Some examples are presented. Finally some conclusions and hints about the possible new developments of these techniques are also given.

Interval-based ranking in noisy evolutionary multiobjective optimization

As one of the most competitive approaches to multi-objective optimization, evolutionary algorithms have been shown to obtain very good results for many realworld multi-objective problems. One of the issues that can affect the performance of these algorithms is the uncertainty in the quality of the solutions which is usually represented with the noise in the objective values. Therefore, handling noisy objectives in evolutionary multi-objective optimization algorithms becomes very important and is gaining more attention in recent years. In this paper we present ?-degree Pareto dominance relation for ordering the solutions in multi-objective optimization when the values of the objective functions are given as intervals. Based on this dominance relation, we propose an adaptation of the non-dominated sorting algorithm for ranking the solutions. This ranking method is then used in a standardmulti-objective evolutionary algorithm and a recently proposed novel multi-objective estimation of distribution algorithm based on joint variable-objective probabilistic modeling, and applied to a set of multi-objective problems with different levels of independent noise. The experimental results show that the use of the proposed method for solution ranking allows to approximate Pareto sets which are considerably better than those obtained when using the dominance probability-based ranking method, which is one of the main methods for noise handling in multi-objective optimization.

Aerodynamic shape optimization of the nose of a high-speed train subjected to crosswind conditions

When dealing with the design of a high-speed train, a multiobjective shape optimization problem is formulated, as these vehicles are object of many aerodynamic problems which are known to be in conflict. More mobility involves an increase in both the cruise speed and lightness, and these requirements directly influence the stability and the ride comfort of the passengers when the train is subjected to a side wind. Thus, crosswind stability plays a more relevant role among the aerodynamic objectives to be optimized. An extensive research activity is observed on aerodynamic response in crosswind conditions.

Optimization methods for the operating room management under uncertainty: stochastic programming vs. decomposition approach

The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.