Essays on European economic and monetary integration

This thesis focuses on two aspects of European economic integration: exchange rate stabilization between non-euro Countries and the Euro Area, and real and nominal convergence of Central and Eastern European Countries. Each Chapter covers these aspects from both a theoretical and empirical perspective. Chapter 1 investigates whether the introduction of the euro was accompanied by a shift in the de facto exchange rate policy of European countries outside the euro area, using methods recently developed by the literature to detect "Fear of Floating" episodes. I find that European Inflation Targeters have tried to stabilize the euro exchange rate, after its introduction; fixed exchange rate arrangements, instead, apart from official policy changes, remained stable. Finally, the euro seems to have gained a relevant role as a reference currency even outside Europe. Chapter 2 proposes an approach to estimate Central Bank preferences starting from the Central Bank's optimization problem within a small open economy, using Sweden as a case study, to find whether stabilization of the exchange rate played a role in the Monetary Policy rule of the Riksbank. The results show that it did not influence interest rate setting; exchange rate stabilization probably occurred as a result of increased economic integration and business cycle convergence. Chapter 3 studies the interactions between wages in the public sector, the traded private sector and the closed sector in ten EU Transition Countries. The theoretical literature on wage spillovers suggests that the traded sector should be the leader in wage setting, with non-traded sectors wages adjusting. We show that large heterogeneity across countries is present, and sheltered and public sector wages are often leaders in wage determination. This result is relevant from a policy perspective since wage spillovers, leading to costs growing faster than productivity, may affect the international cost competitiveness of the traded sector.

Model predictive control in thermal management of multiprocessor systems-on-chip

MultiProcessor Systems-on-Chip (MPSoC) are the core of nowadays and next generation computing platforms. Their relevance in the global market continuously increase, occupying an important role both in everydaylife products (e.g. smartphones, tablets, laptops, cars) and in strategical market sectors as aviation, defense, robotics, medicine. Despite of the incredible performance improvements in the recent years processors manufacturers have had to deal with issues, commonly called “Walls”, that have hindered the processors development. After the famous “Power Wall”, that limited the maximum frequency of a single core and marked the birth of the modern multiprocessors system-on-chip, the “Thermal Wall” and the “Utilization Wall” are the actual key limiter for performance improvements. The former concerns the damaging effects of the high temperature on the chip caused by the large power densities dissipation, whereas the second refers to the impossibility of fully exploiting the computing power of the processor due to the limitations on power and temperature budgets. In this thesis we faced these challenges by developing efficient and reliable solutions able to maximize performance while limiting the maximum temperature below a fixed critical threshold and saving energy. This has been possible by exploiting the Model Predictive Controller (MPC) paradigm that solves an optimization problem subject to constraints in order to find the optimal control decisions for the future interval. A fully-distributedMPC-based thermal controller with a far lower complexity respect to a centralized one has been developed. The control feasibility and interesting properties for the simplification of the control design has been proved by studying a partial differential equation thermal model. Finally, the controller has been efficiently included in more complex control schemes able to minimize energy consumption and deal with mixed-criticalities tasks

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

Ontologies and Methods for Interoperability of Engineering Analysis Models (EAMS) in an E-Design Environment

ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.

Associating optical measurements and estimating orbits of geocentric objects through population-based meta-heuristic methods

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both, the correct associations among the observations and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. The number S corresponds to the number of fences involved in the problem. Each fence consists of a set of observations where each observation belongs to a different object. The S ≥ 3 MTT problem is an NP-hard combinatorial optimization problem. There are two general ways to solve this. One way is to seek the optimum solution, this can be achieved by applying a branch-and- bound algorithm. When using these algorithms the problem has to be greatly simplified to keep the computational cost at a reasonable level. Another option is to approximate the solution by using meta-heuristic methods. These methods aim to efficiently explore the different possible combinations so that a reasonable result can be obtained with a reasonable computational effort. To this end several population-based meta-heuristic methods are implemented and tested on simulated optical measurements. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

OSIA: Out-of-order scheduling for in-order arriving in concurrent multi-path transfer.

One major problem of concurrent multi-path transfer (CMT) scheme in multi-homed mobile networks is that the utilization of different paths with diverse delays may cause packet reordering among packets of the same ?ow. In the case of TCP-like, the reordering exacerbates the problem by bringing more timeouts and unnecessary retransmissions, which eventually degrades the throughput of connections considerably. To address this issue, we ?rst propose an Out-of-order Scheduling for In-order Arriving (OSIA), which exploits the sending time discrepancy to preserve the in-order packet arrival. Then, we formulate the optimal traf?c scheduling as a constrained optimization problem and derive its closedform solution by our proposed progressive water-?lling solution. We also present an implementation to enforce the optimal scheduling scheme using cascaded leaky buckets with multiple faucets, which provides simple guidelines on maximizing the utilization of aggregate bandwidth while decreasing the probability of triggering 3 dupACKs. Compared with previous work, the proposed scheme has lower computation complexity and can also provide the possibility for dynamic network adaptability and ?ner-grain load balancing. Simulation results show that our scheme signi?cantly alleviates reordering and enhances transmission performance.

Leveraging heterogeneity for energy minimization in data centers

Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.

Lifetime maximization for beamforming applications in wireless sensor networks

Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If data is to be sent to a far-away base station, collaborative beamforming by the sensors may help to dis- tribute the load among the nodes and reduce fast battery depletion. However, collaborative beamforming techniques are far from opti- mality and in many cases may be wasting more power than required. In this contribution we consider the issue of energy efficiency in beamforming applications. Using a convex optimization framework, we propose the design of a virtual beamformer that maximizes the network's lifetime while satisfying a pre-specified Quality of Service (QoS) requirement. A distributed consensus-based algorithm for the computation of the optimal beamformer is also provided

Design equations for reinforced concrete members strengthened in shear with external FRP reinforcement formulated in an evolutionary multi-objective framework

Methods for predicting the shear capacity of FRP shear strengthened RC beams assume the traditional approach of superimposing the contribution of the FRP reinforcing to the contributions from the reinforcing steel and the concrete. These methods become the basis for most guides for the design of externally bonded FRP systems for strengthening concrete structures. The variations among them come from the way they account for the effect of basic shear design parameters on shear capacity. This paper presents a simple method for defining improved equations to calculate the shear capacity of reinforced concrete beams externally shear strengthened with FRP. For the first time, the equations are obtained in a multiobjective optimization framework solved by using genetic algorithms, resulting from considering simultaneously the experimental results of beams with and without FRP external reinforcement. The performance of the new proposed equations is compared to the predictions with some of the current shear design guidelines for strengthening concrete structures using FRPs. The proposed procedure is also reformulated as a constrained optimization problem to provide more conservative shear predictions.

La estabilidad del frente de excavación de un túnel en terrenos heterogéneos o con un criterio de rotura no-lineal

El frente de un túnel puede colapsar si la presión aplicada sobre el es inferior a un valor limite denominado presión “critica” o “de colapso”. En este trabajo se desarrolla y presenta un mecanismo de rotura rotacional generado punto a punto para el cálculo de la presión de colapso del frente de túneles excavados en terrenos estratificados o en materiales que siguen un criterio de rotura nolineal. La solución propuesta es una solución de contorno superior en el marco del Análisis Límite y supone una generalización del mecanismo de rotura mas reciente existente en la bibliografía. La presencia de un terreno estratificado o con un criterio de rotura no-lineal implica una variabilidad espacial de las propiedades resistentes. Debido a esto, se generaliza el mecanismo desarrollado por Mollon et al. (2011b) para suelos, de tal forma que se puedan considerar valores locales del ángulo de rozamiento y de la cohesión. Además, la estratificación del terreno permite una rotura parcial del frente, por lo que se implementa esta posibilidad en el mecanismo, siendo la primera solución que emplea un mecanismo de rotura que se ajusta a la estratigrafía del terreno. Por otro lado, la presencia de un material con un criterio de rotura no-lineal exige introducir en el modelo, como variable de estudio, el estado tensional en el frente, el cual se somete al mismo proceso de optimización que las variables geométricas del mecanismo. Se emplea un modelo numérico 3D para validar las predicciones del mecanismo de Análisis Limite, demostrando que proporciona, con un esfuerzo computacional significativamente reducido, buenas predicciones de la presión critica, del tipo de rotura (global o parcial) en terrenos estratificados y de la geometría de fallo. El mecanismo validado se utiliza para realizar diferentes estudios paramétricos sobre la influencia de la estratigrafía en la presión de colapso. Igualmente, se emplea para elaborar cuadros de diseño de la presión de colapso para túneles ejecutados con tuneladora en macizos rocosos de mala calidad y para analizar la influencia en la estabilidad del frente del método constructivo. Asimismo, se lleva a cabo un estudio de fiabilidad de la estabilidad del frente de un túnel excavado en un macizo rocoso altamente fracturado. A partir de el se analiza como afectan las diferentes hipótesis acerca de los tipos de distribución y de las estructuras de correlación a los resultados de fiabilidad. Se investiga también la sensibilidad de los índices de fiabilidad a los cambios en las variables aleatorias, identificando las mas relevantes para el diseño. Por ultimo, se lleva a cabo un estudio experimental mediante un modelo de laboratorio a escala reducida. El modelo representa medio túnel, lo cual permite registrar el movimiento del material mediante una técnica de correlación de imágenes fotográficas. El ensayo se realiza con una arena seca y se controla por deformaciones mediante un pistón que simula el frente. Los resultados obtenidos se comparan con las estimaciones de la solución de Análisis Límite, obteniéndose un ajuste razonable, de acuerdo a la literatura, tanto en la geometría de rotura como en la presión de colapso. A tunnel face may collapse if the applied support pressure is lower than a limit value called the ‘critical’ or ‘collapse’ pressure. In this work, an advanced rotational failure mechanism generated ‘‘point-by-point” is developed to compute the collapse pressure for tunnel faces in layered (or stratified) grounds or in materials that follow a non-linear failure criterion. The proposed solution is an upper bound solution in the framework of limit analysis which extends the most advanced face failure mechanism in the literature. The excavation of the tunnel in a layered ground or in materials with a non-linear failure criterion may lead to a spatial variability of the strength properties. Because of this, the rotational mechanism recently proposed by Mollon et al. (2011b) for Mohr-Coulomb soils is generalized so that it can consider local values of the friction angle and of the cohesion. For layered soils, the mechanism needs to be extended to consider the possibility for partial collapse. The proposed methodology is the first solution with a partial collapse mechanism that can fit to the stratification. Similarly, the use of a nonlinear failure criterion introduces the need to introduce new parameters in the optimization problem to consider the distribution of normal stresses along the failure surface. A 3D numerical model is employed to validate the predictions of the limit analysis mechanism, demonstrating that it provides, with a significantly reduced computational effort, good predictions of critical pressure, of the type of collapse (global or partial) in layered soils, and of its geometry. The mechanism is then employed to conduct parametric studies of the influence of several geometrical and mechanical parameters on face stability of tunnels in layered soils. Similarly, the methodology has been further employed to develop simple design charts that provide the face collapse pressure of tunnels driven by TBM in low quality rock masses and to study the influence of the construction method. Finally, a reliability analysis of the stability of a tunnel face driven in a highly fractured rock mass is performed. The objective is to analyze how different assumptions about distributions types and correlation structures affect the reliability results. In addition, the sensitivity of the reliability index to changes in the random variables is studied, identifying the most relevant variables for engineering design. Finally, an experimental study is carried out using a small-scale laboratory model. The problem is modeled in half, cutting through the tunnel axis vertically, so that displacements of soil particles can be recorded by a digital image correlation technique. The tests were performed with dry sand and displacements are controlled by a piston that supports the soil. The results of the model are compared with the predictions of the Limit Analysis mechanism. A reasonable agreement, according to literature, is obtained between the shapes of the failure surfaces and between the collapse pressures observed in the model tests and computed with the analytical solution.

Arquitectura de supercomputación en la nube para la resolución de problemas de optimización combinatoria

La tesis está focalizada en la resolución de problemas de optimización combinatoria, haciendo uso de las opciones tecnológicas actuales que ofrecen las tecnologías de la información y las comunicaciones, y la investigación operativa. Los problemas de optimización combinatoria se resuelven en general mediante programación lineal y metaheurísticas. La aplicación de las técnicas de resolución de los problemas de optimización combinatoria requiere de una elevada carga computacional, y los algoritmos deben diseñarse, por un lado pensando en la efectividad para encontrar buenas soluciones del problema, y por otro lado, pensando en un uso adecuado de los recursos informáticos disponibles. La programación lineal y las metaheurísticas son técnicas de resolución genéricas, que se pueden aplicar a diferentes problemas, partiendo de una base común que se particulariza para cada problema concreto. En el campo del desarrollo de software, los frameworks cumplen esa función de comenzar un proyecto con el trabajo general ya disponible, con la opción de cambiar o extender ese comportamiento base o genérico, para construir el sistema concreto, lo que permite reducir el tiempo de desarrollo, y amplía las posibilidades de éxito del proyecto. En esta tesis se han desarrollado dos frameworks de desarrollo. El framework ILP permite modelar y resolver problemas de programación lineal, de forma independiente al software de resolución de programación lineal que se utilice. El framework LME permite resolver problemas de optimización combinatoria mediante metaheurísticas. Tradicionalmente, las aplicaciones de resolución de problemas de optimización combinatoria son aplicaciones de escritorio que permiten gestionar toda la información de entrada del problema y resuelven el problema en local, con los recursos hardware disponibles. Recientemente ha aparecido un nuevo paradigma de despliegue y uso de aplicaciones que permite compartir recursos informáticos especializados por Internet. Esta nueva forma de uso de recursos informáticos es la computación en la nube, que presenta el modelo de software como servicio (SaaS). En esta tesis se ha construido una plataforma SaaS, para la resolución de problemas de optimización combinatoria, que se despliega sobre arquitecturas compuestas por procesadores multi-núcleo y tarjetas gráficas, y dispone de algoritmos de resolución basados en frameworks de programación lineal y metaheurísticas. Toda la infraestructura es independiente del problema de optimización combinatoria a resolver, y se han desarrollado tres problemas que están totalmente integrados en la plataforma SaaS. Estos problemas se han seleccionado por su importancia práctica. Uno de los problemas tratados en la tesis, es el problema de rutas de vehículos (VRP), que consiste en calcular las rutas de menor coste de una flota de vehículos, que reparte mercancías a todos los clientes. Se ha partido de la versión más clásica del problema y se han hecho estudios en dos direcciones. Por un lado se ha cuantificado el aumento en la velocidad de ejecución de la resolución del problema en tarjetas gráficas. Por otro lado, se ha estudiado el impacto en la velocidad de ejecución y en la calidad de soluciones, en la resolución por la metaheurística de colonias de hormigas (ACO), cuando se introduce la programación lineal para optimizar las rutas individuales de cada vehículo. Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. Otro de los problemas tratados en la tesis, es el problema de asignación de flotas (FAP), que consiste en crear las rutas de menor coste para la flota de vehículos de una empresa de transporte de viajeros. Se ha definido un nuevo modelo de problema, que engloba características de problemas presentados en la literatura, y añade nuevas características, lo que permite modelar los requerimientos de las empresas de transporte de viajeros actuales. Este nuevo modelo resuelve de forma integrada el problema de definir los horarios de los trayectos, el problema de asignación del tipo de vehículo, y el problema de crear las rotaciones de los vehículos. Se ha creado un modelo de programación lineal para el problema, y se ha resuelto por programación lineal y por colonias de hormigas (ACO). Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. El último problema tratado en la tesis es el problema de planificación táctica de personal (TWFP), que consiste en definir la configuración de una plantilla de trabajadores de menor coste, para cubrir una demanda de carga de trabajo variable. Se ha definido un modelo de problema muy flexible en la definición de contratos, que permite el uso del modelo en diversos sectores productivos. Se ha definido un modelo matemático de programación lineal para representar el problema. Se han definido una serie de casos de uso, que muestran la versatilidad del modelo de problema, y permiten simular el proceso de toma de decisiones de la configuración de una plantilla de trabajadores, cuantificando económicamente cada decisión que se toma. Este problema se ha desarrollado con el framework ILP, y está disponible en la plataforma SaaS. ABSTRACT The thesis is focused on solving combinatorial optimization problems, using current technology options offered by information technology and communications, and operations research. Combinatorial optimization problems are solved in general by linear programming and metaheuristics. The application of these techniques for solving combinatorial optimization problems requires a high computational load, and algorithms are designed, on the one hand thinking to find good solutions to the problem, and on the other hand, thinking about proper use of the available computing resources. Linear programming and metaheuristic are generic resolution techniques, which can be applied to different problems, beginning with a common base that is particularized for each specific problem. In the field of software development, frameworks fulfill this function that allows you to start a project with the overall work already available, with the option to change or extend the behavior or generic basis, to build the concrete system, thus reducing the time development, and expanding the possibilities of success of the project. In this thesis, two development frameworks have been designed and developed. The ILP framework allows to modeling and solving linear programming problems, regardless of the linear programming solver used. The LME framework is designed for solving combinatorial optimization problems using metaheuristics. Traditionally, applications for solving combinatorial optimization problems are desktop applications that allow the user to manage all the information input of the problem and solve the problem locally, using the available hardware resources. Recently, a new deployment paradigm has appeared, that lets to share hardware and software resources by the Internet. This new use of computer resources is cloud computing, which presents the model of software as a service (SaaS). In this thesis, a SaaS platform has been built for solving combinatorial optimization problems, which is deployed on architectures, composed of multi-core processors and graphics cards, and has algorithms based on metaheuristics and linear programming frameworks. The SaaS infrastructure is independent of the combinatorial optimization problem to solve, and three problems are fully integrated into the SaaS platform. These problems have been selected for their practical importance. One of the problems discussed in the thesis, is the vehicle routing problem (VRP), which goal is to calculate the least cost of a fleet of vehicles, which distributes goods to all customers. The VRP has been studied in two directions. On one hand, it has been quantified the increase in execution speed when the problem is solved on graphics cards. On the other hand, it has been studied the impact on execution speed and quality of solutions, when the problem is solved by ant colony optimization (ACO) metaheuristic, and linear programming is introduced to optimize the individual routes of each vehicle. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. Another problem addressed in the thesis, is the fleet assignment problem (FAP), which goal is to create lower cost routes for a fleet of a passenger transport company. It has been defined a new model of problem, which includes features of problems presented in the literature, and adds new features, allowing modeling the business requirements of today's transport companies. This new integrated model solves the problem of defining the flights timetable, the problem of assigning the type of vehicle, and the problem of creating aircraft rotations. The problem has been solved by linear programming and ACO. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. The last problem discussed in the thesis is the tactical planning staff problem (TWFP), which is to define the staff of lower cost, to cover a given work load. It has been defined a very rich problem model in the definition of contracts, allowing the use of the model in various productive sectors. It has been defined a linear programming mathematical model to represent the problem. Some use cases has been defined, to show the versatility of the model problem, and to simulate the decision making process of setting up a staff, economically quantifying every decision that is made. This problem has been developed with the ILP framework, and is available in the SaaS platform.

Sistemas de gestión de puentes : optimización de estrategias de mantenimiento : implementación en redes locales de carreteras

En la actualidad, y en consonancia con la tendencia de “sostenibilidad” extendida a todos los campos y parcelas de la ciencia, nos encontramos con un área de estudio basado en la problemática del inevitable deterioro de las estructuras existentes, y la gestión de las acciones a realizar para mantener las condiciones de servicio de los puentes y prolongar su vida útil. Tal y como se comienza a ver en las inversiones en los países avanzados, con una larga tradición en el desarrollo de sus infraestructuras, se muestra claramente el nuevo marco al que nos dirigimos. Las nuevas tendencias van encaminadas cada vez más a la conservación y mantenimiento, reduciéndose las partidas presupuestarias destinadas a nuevas actuaciones, debido a la completa vertebración territorial que se ha ido instaurando en estos países, entre los que España se encuentra. Este nutrido patrimonio de infraestructuras viarias, que cuentan a su vez con un importante número de estructuras, hacen necesarias las labores de gestión y mantenimiento de los puentes integrantes en las mismas. Bajo estas premisas, la tesis aborda el estado de desarrollo de la implementación de los sistemas de gestión de puentes, las tendencias actuales e identificación de campos por desarrollar, así como la aplicación específica a redes de carreteras de escasos recursos, más allá de la Red Estatal. Además de analizar las diversas metodologías de formación de inventarios, realización de inspecciones y evaluación del estado de puentes, se ha enfocado, como principal objetivo, el desarrollo de un sistema específico de predicción del deterioro y ayuda a la toma de decisiones. Este sistema, adicionalmente a la configuración tradicional de criterios de formación de bases de datos de estructuras e inspecciones, plantea, de forma justificada, la clasificación relativa al conjunto de la red gestionada, según su estado de condición. Eso permite, mediante técnicas de optimización, la correcta toma de decisiones a los técnicos encargados de la gestión de la red. Dentro de los diversos métodos de evaluación de la predicción de evolución del deterioro de cada puente, se plantea la utilización de un método bilineal simplificado envolvente del ajuste empírico realizado y de los modelos markovianos como la solución más efectiva para abordar el análisis de la predicción de la propagación del daño. Todo ello explotando la campaña experimenta realizada que, a partir de una serie de “fotografías técnicas” del estado de la red de puentes gestionados obtenidas mediante las inspecciones realizadas, es capaz de mejorar el proceso habitual de toma de decisiones. Toda la base teórica reflejada en el documento, se ve complementada mediante la implementación de un Sistema de Gestión de Puentes (SGP) específico, adaptado según las necesidades y limitaciones de la administración a la que se ha aplicado, en concreto, la Dirección General de Carreteras de la Junta de Comunidades de Castilla-La Mancha, para una muestra representativa del conjunto de puentes de la red de la provincia de Albacete, partiendo de una situación en la que no existe, actualmente, un sistema formal de gestión de puentes. Tras un meditado análisis del estado del arte dentro de los Capítulos 2 y 3, se plantea un modelo de predicción del deterioro dentro del Capítulo 4 “Modelo de Predicción del Deterioro”. De la misma manera, para la resolución del problema de optimización, se justifica la utilización de un novedoso sistema de optimización secuencial elegido dentro del Capítulo 5, los “Algoritmos Evolutivos”, en sus diferentes variantes, como la herramienta matemática más correcta para distribuir adecuadamente los recursos económicos dedicados a mantenimiento y conservación de los que esta administración pueda disponer en sus partidas de presupuesto a medio plazo. En el Capítulo 6, y en diversos Anexos al presente documento, se muestran los datos y resultados obtenidos de la aplicación específica desarrollada para la red local analizada, utilizando el modelo de deterioro y optimización secuencial, que garantiza la correcta asignación de los escasos recursos de los que disponen las redes autonómicas en España. Se plantea con especial interés la implantación de estos sistemas en la red secundaria española, debido a que reciben en los últimos tiempos una mayor responsabilidad de gestión, con recursos cada vez más limitados. Finalmente, en el Capítulo 7, se plantean una serie de conclusiones que nos hacen reflexionar de la necesidad de comenzar a pasar, en materia de gestión de infraestructuras, de los estudios teóricos y los congresos, hacia la aplicación y la práctica, con un planteamiento que nos debe llevar a cambios importantes en la forma de concebir la labor del ingeniero y las enseñanzas que se imparten en las escuelas. También se enumeran las aportaciones originales que plantea el documento frente al actual estado del arte. Se plantean, de la misma manera, las líneas de investigación en materia de Sistemas de Gestión de Puentes que pueden ayudar a refinar y mejorar los actuales sistemas utilizados. In line with the development of "sustainability" extended to all fields of science, we are faced with the inevitable and ongoing deterioration of existing structures, leading nowadays to the necessary management of maintaining the service conditions and life time extension of bridges. As per the increased amounts of money that can be observed being spent in the countries with an extensive and strong tradition in the development of their infrastructure, the trend can be clearly recognized. The new tendencies turn more and more towards conservation and maintenance, reducing programmed expenses for new construction activities, in line with the already wellestablished territorial structures, as is the case for Spain. This significant heritage of established road infrastructure, consequently containing a vast number of structures, imminently lead to necessary management and maintenance of the including bridges. Under these conditions, this thesis focusses on the status of the development of the management implementation for bridges, current trends, and identifying areas for further development. This also includes the specific application to road networks with limited resources, beyond the national highways. In addition to analyzing the various training methodologies, inventory inspections and condition assessments of bridges, the main objective has been the development of a specific methodology. This methodology, in addition to the traditional system of structure and inspection database training criteria, sustains the classification for the entire road network, according to their condition. This allows, through optimization techniques, for the correct decision making by the technical managers of the network. Among the various methods for assessing the evolution forecast of deterioration of each bridge, a simplified bilinear envelope adjustment made empirical method and Markov models as the most effective solution to address the analysis of predicting the spread of damage, arising from a "technical snapshot" obtained through inspections of the condition of the bridges included in the investigated network. All theoretical basis reflected in the document, is completed by implementing a specific Bridges Management System (BMS), adapted according to the needs and limitations of the authorities for which it has been applied, being in this case particularly the General Highways Directorate of the autonomous region of Castilla-La Mancha, for a representative sample of all bridges in the network in the province of Albacete, starting from a situation where there is currently no formal bridge management system. After an analysis of the state of the art in Chapters 2 and 3, a new deterioration prediction model is developed in Chapter 4, "Deterioration Prediction Model". In the same way, to solve the optimization problem is proposed the use of a singular system of sequential optimization elected under Chapter 5, the "Evolutionary Algorithms", the most suitable mathematical tool to adequately distribute the economic resources for maintenance and conservation for mid-term budget planning. In Chapter 6, and in the various appendices, data and results are presented of the developed application for the analyzed local network, from the optimization model, which guarantees the correct allocation of scarce resources at the disposal of authorities responsible for the regional networks in Spain. The implementation of these systems is witnessed with particular interest for the Spanish secondary network, because of the increasing management responsibility, with decreasing resources. Chapter 7 presents a series of conclusions that triggers to reconsider shifting from theoretical studies and conferences towards a practical implementation, considering how to properly conceive the engineering input and the related education. The original contributions of the document are also listed. In the same way, the research on the Bridges Management System can help evaluating and improving the used systematics.

Desarrollo de un Procedimiento Basado en Algoritmos de Optimización para el Dimensionado de Absorbedores Puntuales Aplicados a la Conversión de Energía Undimotriz

La energía transportada por el oleaje a través de los océanos (energía undimotriz) se enmarca dentro de las denominadas energías oceánicas. Su aprovechamiento para generar energía eléctrica (o ser aprovechada de alguna otra forma) es una idea reflejada ya hace más de dos siglos en una patente (1799). Desde entonces, y con especial intensidad desde los años 70, ha venido despertando el interés de instituciones ligadas al I+D+i y empresas del sector energético y tecnológico, debido principalmente a la magnitud del recurso disponible. Actualmente se puede considerar al sector en un estado precomercial, con un amplio rango de dispositivos y tecnologías en diferente grado de desarrollo en los que ninguno destaca sobre los otros (ni ha demostrado su viabilidad económica), y sin que se aprecie una tendencia a converger un único dispositivo (o un número reducido de ellos). El recurso energético que se está tratando de aprovechar, pese a compartir la característica de no-controlabilidad con otras fuentes de energía renovable como la eólica o la solar, presenta una variabilidad adicional. De esta manera, diferentes localizaciones, pese a poder presentar recursos de contenido energético similar, presentan oleajes de características muy diferentes en términos de alturas y periodos de oleaje, y en la dispersión estadística de estos valores. Esta variabilidad en el oleaje hace que cobre especial relevancia la adecuación de los dispositivos de aprovechamiento de energía undimotriz (WEC: Wave Energy Converter) a su localización, de cara a mejorar su viabilidad económica. Parece razonable suponer que, en un futuro, el proceso de diseño de un parque de generación undimotriz implique un rediseño (en base a una tecnología conocida) para cada proyecto de implantación en una nueva localización. El objetivo de esta tesis es plantear un procedimiento de dimensionado de una tecnología de aprovechamiento de la energía undimotriz concreta: los absorbedores puntuales. Dicha metodología de diseño se plantea como un problema de optimización matemático, el cual se resuelve utilizando un algoritmo de optimización bioinspirado: evolución diferencial. Este planteamiento permite automatizar la fase previa de dimensionado implementando la metodología en un código de programación. El proceso de diseño de un WEC es un problema de ingería complejo, por lo que no considera factible el planteamiento de un diseño completo mediante un único procedimiento de optimización matemático. En vez de eso, se platea el proceso de diseño en diferentes etapas, de manera que la metodología desarrollada en esta tesis se utilice para obtener las dimensiones básicas de una solución de referencia de WEC, la cual será utilizada como punto de partida para continuar con las etapas posteriores del proceso de diseño. La metodología de dimensionado previo presentada en esta tesis parte de unas condiciones de contorno de diseño definidas previamente, tales como: localización, características del sistema de generación de energía eléctrica (PTO: Power Take-Off), estrategia de extracción de energía eléctrica y concepto concreto de WEC). Utilizando un algoritmo de evolución diferencial multi-objetivo se obtiene un conjunto de soluciones factibles (de acuerdo con una ciertas restricciones técnicas y dimensionales) y óptimas (de acuerdo con una serie de funciones objetivo de pseudo-coste y pseudo-beneficio). Dicho conjunto de soluciones o dimensiones de WEC es utilizado como caso de referencia en las posteriores etapas de diseño. En el documento de la tesis se presentan dos versiones de dicha metodología con dos modelos diferentes de evaluación de las soluciones candidatas. Por un lado, se presenta un modelo en el dominio de la frecuencia que presenta importantes simplificaciones en cuanto al tratamiento del recurso del oleaje. Este procedimiento presenta una menor carga computacional pero una mayor incertidumbre en los resultados, la cual puede traducirse en trabajo adicional en las etapas posteriores del proceso de diseño. Sin embargo, el uso de esta metodología resulta conveniente para realizar análisis paramétricos previos de las condiciones de contorno, tales como la localización seleccionada. Por otro lado, la segunda metodología propuesta utiliza modelos en el domino estocástico, lo que aumenta la carga computacional, pero permite obtener resultados con menos incertidumbre e información estadística muy útil para el proceso de diseño. Por este motivo, esta metodología es más adecuada para su uso en un proceso de dimensionado completo de un WEC. La metodología desarrollada durante la tesis ha sido utilizada en un proyecto industrial de evaluación energética preliminar de una planta de energía undimotriz. En dicho proceso de evaluación, el método de dimensionado previo fue utilizado en una primera etapa, de cara a obtener un conjunto de soluciones factibles de acuerdo con una serie de restricciones técnicas básicas. La selección y refinamiento de la geometría de la solución geométrica de WEC propuesta fue realizada a posteriori (por otros participantes del proyecto) utilizando un modelo detallado en el dominio del tiempo y un modelo de evaluación económica del dispositivo. El uso de esta metodología puede ayudar a reducir las iteraciones manuales y a mejorar los resultados obtenidos en estas últimas etapas del proyecto. ABSTRACT The energy transported by ocean waves (wave energy) is framed within the so-called oceanic energies. Its use to generate electric energy (or desalinate ocean water, etc.) is an idea expressed first time in a patent two centuries ago (1799). Ever since, but specially since the 1970’s, this energy has become interesting for R&D institutions and companies related with the technological and energetic sectors mainly because of the magnitude of available energy. Nowadays the development of this technology can be considered to be in a pre-commercial stage, with a wide range of devices and technologies developed to different degrees but with none standing out nor economically viable. Nor do these technologies seem ready to converge to a single device (or a reduce number of devices). The energy resource to be exploited shares its non-controllability with other renewable energy sources such as wind and solar. However, wave energy presents an additional short-term variability due to its oscillatory nature. Thus, different locations may show waves with similar energy content but different characteristics such as wave height or wave period. This variability in ocean waves makes it very important that the devices for harnessing wave energy (WEC: Wave Energy Converter) fit closely to the characteristics of their location in order to improve their economic viability. It seems reasonable to assume that, in the future, the process of designing a wave power plant will involve a re-design (based on a well-known technology) for each implementation project in any new location. The objective of this PhD thesis is to propose a dimensioning method for a specific wave-energy-harnessing technology: point absorbers. This design methodology is presented as a mathematical optimization problem solved by using an optimization bio-inspired algorithm: differential evolution. This approach allows automating the preliminary dimensioning stage by implementing the methodology in programmed code. The design process of a WEC is a complex engineering problem, so the complete design is not feasible using a single mathematical optimization procedure. Instead, the design process is proposed in different stages, so the methodology developed in this thesis is used for the basic dimensions of a reference solution of the WEC, which would be used as a starting point for the later stages of the design process. The preliminary dimensioning methodology presented in this thesis starts from some previously defined boundary conditions such as: location, power take-off (PTO) characteristic, strategy of energy extraction and specific WEC technology. Using a differential multi-objective evolutionary algorithm produces a set of feasible solutions (according to certain technical and dimensional constraints) and optimal solutions (according to a set of pseudo-cost and pseudo-benefit objective functions). This set of solutions or WEC dimensions are used as a reference case in subsequent stages of design. In the document of this thesis, two versions of this methodology with two different models of evaluation of candidate solutions are presented. On the one hand, a model in the frequency domain that has significant simplifications in the treatment of the wave resource is presented. This method implies a lower computational load but increased uncertainty in the results, which may lead to additional work in the later stages of the design process. However, use of this methodology is useful in order to perform previous parametric analysis of boundary conditions such as the selected location. On the other hand, the second method uses stochastic models, increasing the computational load, but providing results with smaller uncertainty and very useful statistical information for the design process. Therefore, this method is more suitable to be used in a detail design process for full dimensioning of the WEC. The methodology developed throughout the thesis has been used in an industrial project for preliminary energetic assessment of a wave energy power plant. In this assessment process, the method of previous dimensioning was used in the first stage, in order to obtain a set of feasible solutions according to a set of basic technical constraints. The geometry of the WEC was refined and selected subsequently (by other project participants) using a detailed model in the time domain and a model of economic evaluation of the device. Using this methodology can help to reduce the number of design iterations and to improve the results obtained in the last stages of the project.

Optimización del consumo de combustible de un vehículo dependiendo de las condiciones de la carretera

El consumo de combustible en un automóvil es una característica que se intenta mejorar continuamente debido a los precios del carburante y a la creciente conciencia medioambiental. Esta tesis doctoral plantea un algoritmo de optimización del consumo que tiene en cuenta las especificaciones técnicas del vehículo, el perfil de orografía de la carretera y el tráfico presente en ella. El algoritmo de optimización calcula el perfil de velocidad óptima que debe seguir el vehículo para completar un recorrido empleando un tiempo de viaje especificado. El cálculo del perfil de velocidad óptima considera los valores de pendiente de la carretera así como también las condiciones de tráfico vehicular de la franja horaria en que se realiza el recorrido. El algoritmo de optimización reacciona ante condiciones de tráfico cambiantes y adapta continuamente el perfil óptimo de velocidad para que el vehículo llegue al destino cumpliendo el horario de llegada establecido. La optimización de consumo es aplicada en vehículos convencionales de motor de combustión interna y en vehículos híbridos tipo serie. Los datos de consumo utilizados por el algoritmo de optimización se obtienen mediante la simulación de modelos cuasi-estáticos de los vehículos. La técnica de minimización empleada por el algoritmo es la Programación Dinámica. El algoritmo divide la optimización del consumo en dos partes claramente diferenciadas y aplica la Programación Dinámica sobre cada una de ellas. La primera parte corresponde a la optimización del consumo del vehículo en función de las condiciones de tráfico. Esta optimización calcula un perfil de velocidad promedio que evita, cuando es posible, las retenciones de tráfico. El tiempo de viaje perdido durante una retención de tráfico debe recuperarse a través de un aumento posterior de la velocidad promedio que incrementaría el consumo del vehículo. La segunda parte de la optimización es la encargada del cálculo de la velocidad óptima en función de la orografía y del tiempo de viaje disponible. Dado que el consumo de combustible del vehículo se incrementa cuando disminuye el tiempo disponible para finalizar un recorrido, esta optimización utiliza factores de ponderación para modular la influencia que tiene cada una de estas dos variables en el proceso de minimización. Aunque los factores de ponderación y la orografía de la carretera condicionan el nivel de ahorro de la optimización, los perfiles de velocidad óptima calculados logran ahorros de consumo respecto de un perfil de velocidad constante que obtiene el mismo tiempo de recorrido. Las simulaciones indican que el ahorro de combustible del vehículo convencional puede lograr hasta un 8.9% mientras que el ahorro de energía eléctrica del vehículo híbrido serie un 2.8%. El algoritmo fusiona la optimización en función de las condiciones del tráfico y la optimización en función de la orografía durante el cálculo en tiempo real del perfil óptimo de velocidad. La optimización conjunta se logra cuando el perfil de velocidad promedio resultante de la optimización en función de las condiciones de tráfico define los valores de los factores de ponderación de la optimización en función de la orografía. Aunque el nivel de ahorro de la optimización conjunta depende de las condiciones de tráfico, de la orografía, del tiempo de recorrido y de las características propias del vehículo, las simulaciones indican ahorros de consumo superiores al 6% en ambas clases de vehículo respecto a optimizaciones que no logran evitar retenciones de tráfico en la carretera. ABSTRACT Fuel consumption of cars is a feature that is continuously being improved due to the fuel price and an increasing environmental awareness. This doctoral dissertation describes an optimization algorithm to decrease the fuel consumption taking into account the technical specifications of the vehicle, the terrain profile of the road and the traffic conditions of the trip. The algorithm calculates the optimal speed profile that completes a trip having a specified travel time. This calculation considers the road slope and the expected traffic conditions during the trip. The optimization algorithm is also able to react to changing traffic conditions and tunes the optimal speed profile to reach the destination within the specified arrival time. The optimization is applied on a conventional vehicle and also on a Series Hybrid Electric vehicle (SHEV). The fuel consumption optimization algorithm uses data obtained from quasi-static simulations. The algorithm is based on Dynamic Programming and divides the fuel consumption optimization problem into two parts. The first part of the optimization process reduces the fuel consumption according to foreseeable traffic conditions. It calculates an average speed profile that tries to avoid, if possible, the traffic jams on the road. Traffic jams that delay drivers result in higher vehicle speed to make up for lost time. A higher speed of the vehicle within an already defined time scheme increases fuel consumption. The second part of the optimization process is in charge of calculating the optimal speed profile according to the road slope and the remaining travel time. The optimization tunes the fuel consumption and travel time relevancies by using two penalty factors. Although the optimization results depend on the road slope and the travel time, the optimal speed profile produces improvements of 8.9% on the fuel consumption of the conventional car and of 2.8% on the spent energy of the hybrid vehicle when compared with a constant speed profile. The two parts of the optimization process are combined during the Real-Time execution of the algorithm. The average speed profile calculated by the optimization according to the traffic conditions provides values for the two penalty factors utilized by the second part of the optimization process. Although the savings depend on the road slope, traffic conditions, vehicle features, and the remaining travel time, simulations show that this joint optimization process can improve the energy consumption of the two vehicles types by more than 6%.