The objective of this thesis is to apply alternative multi-objective optimization techniques to the portfolio selection problem. Theoretical part starts with detailed analysis of the classical Markowitz model and its assumptions. Following that, introduction of multi-criterion optimization techniques available for finding non-dominated portfolios is given. One of these techniques, the genetic algorithm, is presented in great detail. Some of the basic methods useful for predicting stock prices and its risks are presented at the end of the theoretical part. Practical part presents an application of the theory to the problem of constructing efficient portfolios of 11 selected stocks traded on Prague Stock Exchange. Results achieved by different approaches are compared and interpreted.

Thesis on the topic Comparison of cashback portal and suggestions on its improvement in a specific organization"deals with the comparison of the three cashback portals (PlnaPenezenka.cz, VratnéPeníze.cz and TopCashback.uk), and also proposals to improve the cashback Portal PlnaPenezenka.cz. The theoretical part is mainly focused on online marketing and its selected tools (SEO, e-mailing, PPC, affiliate marketing, etc.). In the next part of the theoretical part is introduced to web design and its trends 2015 and also elements for easy web site for the user. In the practical part is first introduced to small emerging company 5DM.cz and its three main projects-discount aggregator TopSleva.cz, affiliate network, Affiliate Club cashback Portal PlnaPenezenka.cz. On the comparison of three cashback portals PlnaPenezenka.cz, URVratnéPeníze.cz, and TopCashback.uk, with the addition of the word comparison drawn comparisons using multi-criteria decision making method of the weighted rating. Another part of the practical work is focused on proposals for improving the cashback Portal PlnaPenezenka.cz, with the aim of improving the services for users, attract new users, which is related to the increase of the profit of the company 5DM.cz and also differentiate from other Czech cashback portals and popular long foreign cashback portals, for example. TopCashback.uk or Quidco.com.

Decision making is an essential activity for humans and often becomes complex in the presence of uncertainty or insufficient knowledge. This research aims at estimating preferences using pairwise comparisons. A decision maker uses pairwise comparison when he/she is unable to directly assign criteria weights or scores to the available options. The judgments provided in pairwise comparisons may not always be consistent for several reasons. Experimentation has been used to obtain statistical evidence related to the widely-used consistency measures. The results highlight the need to propose new consistency measures. Two new consistency measures - termed congruence and dissonance - are proposed to aid the decision maker in the process of elicitation. Inconsistencies in pairwise comparisons are of two types i.e. cardinal and ordinal. It is shown that both cardinal and ordinal consistency can be improved with the help of these two measures. A heuristic method is then devised to detect and remove intransitive judgments. The results suggest that the devised method is feasible for improving ordinal consistency and is computationally more efficient than the optimization-based methods. There exist situations when revision of judgments is not allowed and prioritization is required without attempting to remove inconsistency. A new prioritization method has been proposed using the graph-theoretic approach. Although the performance of the proposed prioritization method was found to be comparable to other approaches, it has practical limitation in terms of computation time. As a consequence, the problem of prioritization is explored as an optimization problem. A new method based on multi-objective optimization is formulated that offers multiple non-dominated solutions and outperforms all other relevant methods for inconsistent set of judgments. A priority estimation tool (PriEsT) has been developed that implements the proposed consistency measures and prioritization methods. In order to show the benefits of PriEsT, a case study involving Telecom infrastructure selection is presented.

Optimisation is one of the most important and challenging part of any engineering design. In real world design problems one faces multiobjective optimisation under constraints. The optimal solution in these cases is not unique because the objectives can contradict each other. In such cases, a set of optimal solutions which forms a Pareto frontier in the objective space is considered. There are many algorithms to generate the Pareto frontier. However, only a few of them are potentially capable of providing an evenly distributed set of the solutions. Such a property is especially important in real-life design because a decision maker is usually able to analyse only a very limited quantity of solutions. This thesis consists of two main parts. At first, it develops and gives the detailed description of two different algorithms that are able to generate an evenly distributed Pareto set in a general formulation. One is a classical approach and called Directed Search Domain (DSD) and the other, the cylindrical constraint evolutionary algorithm (CCEA), is a hybrid population based method. The efficiency of the algorithms are demonstrated by a number of challenging test cases and the comparisons with the results of the other existing methods. It is shown that the proposed methods are successful in generating the Pareto solutions even when some existing methods fail. In real world design problems, deterministic approaches cannot provide a reliable solution as in the event of uncertainty, deterministic optimal solution would be infeasible in many instances. Therefore a solution less sensitive to problem perturbation is desirable. This leads to the robust solution which is the focus of the second part of the thesis. In the literature, there are some techniques tailored for robust optimisation. However, most of them are either computationally expensive or do not systematically articulate the designer preferences into a robust solution. In this thesis, by introducing a measure for robustness in multiobjective context, a tunable robust function (TRF) is presented. Including the TRF in the problem formulation, it is demonstrated that the desirable robust solution based on designer preferences can be obtained. This not only provides the robust solution but also gives a control over the robustness level. The method is efficient as it only increases the dimension of the problem by one irrespective of the dimension of the original problem.

Orientador: Paulo Augusto Valente Ferreira / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-24T07:32:44Z (GMT). No. of bitstreams: 1 Fontanini_Walcir_D.pdf: 1375688 bytes, checksum: e26761ae454a5f51d8d316afa0718881 (MD5) Previous issue date: 2013 / Resumo: O problema de programação de serviços web é considerado. O processo de tomada de decisão em ambientes de negócios web, descritos por tarefas sequenciais e/ou paralelas, envolve selecionar fornecedores de forma ótima dentre um conjunto potencial de provedores de serviços. Características dos serviços como custo, duração de execução, confiabilidade, disponibilidade e reputação são tratadas como múltiplos objetivos a atingir. Inicialmente, a escolha de provedores é feita por Otimização Multi-Objetivo Inteira-Mista, mais especificamente por meio de um modelo de Programação Alvo. Em seguida, o problema de programação de serviços passa a ser tratado no contexto da Teoria dos Jogos, como um jogo envolvendo provedores que buscam maximizar suas utilidades. Diferentes hipóteses sobre a interação entre provedores dão origem a diferentes noções de equilíbrio: Equilíbrio de Nash, Equilíbrio Correlacionado e Equilíbrio de Bayes-Nash. Finalmente, o problema de programação de serviços é modelado como um problema de Leilão de Segundo Preço, o Mecanismo de Leilão Vickrey-Clark-Grooves. A tese inclui exemplos numéricos ilustrativos para todos os modelos propostos / Abstract: The web services scheduling problem is considered. The decision making process in web-based business environments, described by sequential and/or parallel tasks, involves the optimal selection of suppliers over a set of potential service providers. Characteristics as cost, execution duration, reliability, availability and reputation are treated as multiple objectives to be reached. Initially, the selection of suppliers is performed by Mixed-Integer Multi-Objective Optimization, more specifically, by means of a Goal Programming model. Subsequently, the web services scheduling problem is handled in the Game Theory framework, as a game played by suppliers who aim at maximizing their own utilities. Different hypothesis about the interaction between the suppliers give rise to different equilibrium solutions: Nash Equilibrium, Correlated Equilibrium and Bayes-Nash Equilibrium. Finally, the web services scheduling problem is modeled as a Second Price Auction, the Vickrey-Clark-Grooves Auction Mechnism. The thesis includes illustrative numerical examples for all the models proposed / Doutorado / Automação / Doutor em Engenharia Elétrica

Orientadores: Ieda Geriberto Hidalgo, Paulo de Barros Correia / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-27T18:22:11Z (GMT). No. of bitstreams: 1 Fernandes_JessicaPillonTorralba_D.pdf: 6009989 bytes, checksum: a3f55f4b7f91827762cdfb4e83ebcf4c (MD5) Previous issue date: 2015 / Resumo: Em busca do desenvolvimento sustentável, a atividade de produção de energia iniciou o século XXI com foco em dois temas: eficiência energética e utilização de fontes de energia renováveis. O Brasil é um país privilegiado em termos de disponibilidade de recursos naturais para a geração de energia, principalmente através da água. Apesar da evolução de outras fontes renováveis de energia, como a biomassa e a eólica, é previsto um aumento da utilização de energia hidráulica na geração de eletricidade de forma sustentável. Para acompanhar esse aumento, existe a necessidade de expandir a oferta de energia através da instalação de novas usinas hidrelétricas e/ou otimização da operação das usinas hidrelétricas existentes. Neste contexto, esta tese apresenta uma metodologia para resolver o problema de despacho dinâmico de máquinas e geração com horizonte diário e discretização horária. Ela baseia-se na Programação por Metas Lexicográficas, utilizando Algoritmo Genético e Strength Pareto Evolutionary Algorithm. A formulação matemática do problema possui dois objetivos conflitantes. O primeiro consiste em maximizar a geração líquida da usina ao longo do dia. O segundo visa minimizar o número de partidas e paradas das unidades geradoras. A resolução é executada em duas etapas. Na Etapa 1, o Algoritmo Genético é utilizado para resolver o problema estático para cada hora. Na Etapa 2, Algoritmo Genético e Strength Pareto Evolutionary Algorithm são empregados para solucionar o problema dinâmico ao longo de um dia. As soluções encontradas são analisadas através da construção de uma curva de trade-offs. Os estudos de casos são realizados com as usinas Jupiá e Porto Primavera ,que pertencem ao Sistema Interligado Nacional. Os resultados mostram que a metodologia proposta apresenta soluções eficientes e econômicas para a programação diária de usinas hidrelétricas / Abstract: In pursuit of the sustainable development, the energy production activity began the 21st century with focus on two themes: energy efficiency and use of renewable energy sources. Brazil is a privileged country in terms of availability of natural resources to energy production, mainly through water. Despite the development of other renewable energy sources, such as biomass and wind power, hydro energy is expected to increase in the electricity generation in a sustainable way. To keep this growing, there is a need to increase the supply of energy by installing new hydroelectric plants and/or optimizing the operation of existing ones. In this context, this thesis presents a methodology to solve the dynamic dispatch problem of units and generation with a daily horizon and hourly discretization. It is based on Lexicographic Goal Programming using Genetic Algorithm and Strength Pareto Evolutionary Algorithm. The mathematical formulation of the problem has two conflicting goals. The first consists of maximizing the electric power output the plant throughout the day. The second aims to minimize the number of start-ups and shut-downs of the generating units. The resolution is divided in two steps. In Step 1, Genetic Algorithm is used to solve the static problem for each hour. Phase 2 employs Genetic Algorithm and Strength Pareto Evolutionary Algorithm to solve the dynamic problem throughout the day. The solutions are analyzed by building a trade-offs curve. The case studies are carried out with Jupiá and Porto Primavera hydroelectric power plants that belong to the National Interconnected System. The results show that the proposed methodology provides efficient and economic solutions for the daily operation of hydroelectric power plants / Doutorado / Planejamento de Sistemas Energeticos / Doutora em Planejamento de Sistemas Energéticos

Esta tesis investiga el problema de gestión de tesorería desde un punto de vista multidimensional. La gestión de tesorería trata de equilibrar la cantidad que se mantiene en efectivo y la que se dedica a inversiones a corto plazo. Normalmente, los tesoreros toman decisiones basándose en el nivel óptimo de tesorería por motivos operativos y de precaución. En esta tesis exploramos las oportunidades para mejorar la toma decisiones derivadas de modelar la incertidumbre presente en los flujos de caja con la ayuda de procedimientos basados en datos en un entorno multiobjetivo. Por un lado, los tesoreros pueden conseguir ahorros a través de la previsión de tesorería. Para ello, realizamos un estudio empírico con el objetivo de aprovechar las más recientes técnicas de aprendizaje automático como paso clave para conectar el análisis de los datos disponibles con los procesos de optimización en la gestión de tesorería. Por otro lado, los tesoreros pueden estar interesados no solo en el coste sino también en al riesgo asociado a sus decisiones. Por esta razón, tratamos el problema de gestión de tesorería desde una perspectiva multiobjetivo, considerando tanto el coste como el riesgo. Además, debido a la cambiante situación financiera actual, exploramos la selección de modelos de gestión de tesorería en función de diferentes condiciones operativas y de su robustez. También demostramos la utilidad de las previsiones a través de un nuevo modelo de gestión de tesorería que mejora el estado del arte al garantizar soluciones óptimas. Como la mayoría de las empresas trabaja con sistemas de tesorería con múltiples cuentas bancarias, desarrollamos un marco para la formulación y solución del problema de gestión de tesorería con múltiples cuentas bancarias. Finalmente, en un intento de acercar teoría y práctica, también ofrecemos una librería de software en Python para usuarios interesados en la construcción de sistemas de ayuda a la toma de decisiones en gestión de tesorería. / This thesis investigates the cash management problem from a multidimensional perspective. Cash management focuses on finding the balance between cash holdings and short-term investments. Typically, cash managers make decisions based usually on a firm's optimal cash balance for operational and precautionary purposes. We here explore the opportunities for improved decision-making derived from modeling cash flow uncertainty with the help of data-driven procedures within a multiobjective context. On the one hand, cash managers may achieve cost savings by forecasting future cash flows. To this end, we perform an empirical analysis of daily cash flow time-series to take advantage of modern machine learning techniques as a key step to connect data analysis and optimization methods in cash management. On the other hand, cash managers may be interested not only in the cost but also in the risk associated to decision-making. Thus, we address the cash management problem from a multiobjective perspective focusing on both cost and risk. In addition, under the current situation of time-varying financial circumstances, the selection of cash management models according to operating conditions and its robustness are worth considering questions. We also show the utility of forecasts through a new cash management model which outperforms the state-of-the-art by guaranteeing optimal solutions. Since most firms usually deal with cash management systems with multiple accounts, we develop a framework to formulate and solve the multiple bank accounts cash management problem. Finally, in an attempt to fill the gap between theory and practice, we also provide a software library in Python for practitioners interested in building decision support systems for cash management. / Esta tesi investiga el problema de gestió de tresoreria des d'un punt de vista multidimensional. La gestió de tresoreria tracta d'equilibrar la quantitat que es manté en efectiu i la que es dedica a inversions a curt termini. Normalment, el tresorers prenen decisions basant-se en el nivell òptim de tresoreria per motius operatius i de precaució. En aquesta tesi explorem les oportunitats per millorar la presa de decisions derivades de modelitzar la incertesa present en els fluxos de caixa amb l'ajuda de procediments basats en dades. Per un costat, els tresorers poden aconseguir estalvis de costos mitjançant la previsió de tresoreria. Per tal d'aconseguir-ho, realitzem d'un estudi empíric amb l'objectiu d'aprofitar les més recents tècniques d'aprenentatge automàtic per connectar l'anàlisi de les dades disponbiles amb els procesos d'optimització en la gestió de tresoreria. Per altra banda, els tresorers poden estar interessats no sols en el cost sinó també en el risc associat a les seues decisions. Per tant, tractem el problema de gestió de tresoreria des d'un punt de vista multiobjectiu, fixant-se tant en el cost com en el risc. A més a més, degut a la canviant situació financera actual, explorem la selecció de models de gestió de tresoreria en funció de diferents condicions operatives i de la seua robustesa. També demostrem la utilitat de les previsions mitjançant un nou model de tresoreria que millora l'estat de l'art al garantir solucions òptimes. Com que la majoria d'empreses treballa amb sistemes de tresoreria amb múltiples comptes bancaris, desenvolupem un marc per a la formulació i solució del problema de gestió de tresoreria amb múltiples comptes bancaris. Finalment, en un intent d'apropar teoria i pràctica, també oferim un llibreria en Python per a usuaris interessats en la construcció de sistemes d'ajuda a la presa de decisions en la gestió de tresoreria. / Salas Molina, F. (2017). DATA-DRIVEN DECISION-MAKING AND ITS APPLICATION TO THE CORPORATE CASH MANAGEMENT PROBLEM [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/95408 / TESIS

The work is aimed to propose a methodology for creating an equivalent of composite materials used for construction of small aircraft. Such equivalent should enable to create numerical models of small aircraft in the simulation of precertication EMC tests for aircraft resistance against the lightning. Eliminating situations threatening the aircraft and passengers in the initial steps of the design will allow savings in production costs and contribute to the safety of air transport. In order to nd the equivalent of composite materials, global optimization methods will be used.

Multiobjective optimization system of exhaust manifold shapes including initial design has been developed. Space of possible solutions is explored by an evolutionary algorithm. Evaluation of exhaust drains shape comes  from drains length and sum of arc angles. Drains mustn't interfere in surrounding parts. System is tested on set of input data originated from practice. Further, performance of proposed evolutionary algorithm is evaluated.

Orientador: Antonio Roberto Balbo / Resumo: A produção de energia eólica tem se destacado no Brasil e mostrado grande importância na questão ambiental, pois auxilia na redução da emissão dos gases poluentes na atmosfera, provenientes de outras fontes de energia. Neste trabalho é proposta uma modelagem matemática de otimização multiobjetivo a qual explora a produção de energia eólica em um problema de despacho econômico e ambiental termo-eólico. O principal objetivo é mostrar que uma metodologia determinística envolvendo os métodos de otimização multiobjetivo de restrições canalizadas progressivas e de técnicas de programação por metas ponderadas, em conjunto com o método de pontos interiores, é eficiente à resolução deste problema. É proposta uma nova técnica, a qual é uma combinação entre os métodos de otimização multiobjetivo citados. As soluções dos subproblemas gerados por estes métodos serão determinadas através de pacotes computacionais, onde são apresentados resultados de casos distintos de produção de energia, mostrando a insuficiência da energia eólica nos custos operacionais da geração e no impacto ambiental / Abstract: The production of wind energy has stood out in Brazil and has shown great importance in the environmental issue, as it assists to reduce of polluting gases in the atmosphere arising out of other sources of energy. In this work a mathematical modeling of optimization multiobjective is proposed, which explores the wind energy production in a thermal-wind environmental and economic dispatch problem. The main objective is to show that a deterministic methodology involving the multiobjective optimization methods, progressive bounded constraints and weighted goal programming techniques, together with an interior point method, is e cient to solve this problem. A new technique is proposed, which is a combination of the mentioned multiobjective optimization methods. The solutions of the generated subproblems by these methods will be determined through of computational package and the results of distinct cases of energy production will be presented, showing the in uence of the wind power on the generation and on the environmental impact. / Doutor