O estudo da substituição de bens de capital proporciona a empresa uma visão sobre a vida útil dos seus bens e oportuniza o planejamento para efetuar, dentro de um tempo ótimo, a troca do bem atual por um substituto que possa oferecer vantagens no que diz respeito a custos de operação e manutenção, sendo possível obter com isso a maximização das receitas. Esta dissertação propõe um modelo para a avaliação da vida útil econômica de máquinas e equipamentos fazendo uso da programação dinâmica (PD) com a geração de números aleatórios por meio do método de Monte Carlo (MMC). O modelo contempla a definição das variáveis que serão utilizadas, a aplicação do método de Monte Carlo às variáveis, o cálculo dos valores presentes, os cálculos da programação dinâmica com o objetivo de definir a máxima receita, o desenvolvimento da programação com o uso do software MatLab e a validação do modelo. As simulações foram realizadas utilizando as taxas de desconto baseadas no IPCA, CDI, IGP-M, Selic e meta Selic. A utilização do método de Monte Carlo possibilitou a geração de uma série de políticas para cada simulação, sendo estas analisadas estatisticamente como forma de verificar aquela que melhor representaria a política de substituição e consequentemente definisse a vida útil econômica do bem. O modelo foi aplicado a um centro de usinagem vertical e demonstrou flexibilidade na informação dos dados de entrada ao se utilizar a programação no software MatLab. Observou-se que além de gerar uma gama de possibilidades o modelo PD+MMC pode auxiliar o tomador de decisão quanto a estratégia a ser utilizada na substituição da máquina. Os cálculos efetuados por meio do modelo PD+MMC, para um horizonte de planejamento de 15 anos, utilizando as cinco taxas de desconto, forneceram políticas de substituição com estimativas de vida útil econômica de 3 anos para as taxas CDI, Selic e meta Selic e vida útil superior a 15 anos para as taxas IPCA e IGP-M. Por meio das análises estatísticas foi possível definir que a política de substituição que apresentou maior confiabilidade foi a que utilizou o IPCA/IBGE, a qual gerou a maior receita e a maior vida útil da máquina, superior a 16 anos, apresentando significância de 77,56% para a frequência de políticas. / Submitted by Ana Guimarães Pereira (agpereir@ucs.br) on 2017-08-28T11:15:02Z No. of bitstreams: 1 Dissertacao Ricardo Plizzari.pdf: 2804449 bytes, checksum: 020b648827a0a91276c93b1a078bd672 (MD5) / Made available in DSpace on 2017-08-28T11:15:02Z (GMT). No. of bitstreams: 1 Dissertacao Ricardo Plizzari.pdf: 2804449 bytes, checksum: 020b648827a0a91276c93b1a078bd672 (MD5) Previous issue date: 2017-08-24 / The replacement study of capital goods provides to the company an overview about the useful life of its assets and provides planning for effecting, within an optimal time, the exchange of the present good by a substitute that may offer advantages with respect to Costs of operation and maintenance, being possible to obtain the maximization of revenues. This dissertation proposes a model for evaluation of economic useful life of machines and equipment making use of dynamic programming (PD) with the generation of random numbers by the Monte Carlo method (MMC). The model includes variables definition that will be used, the application of the Monte Carlo method to the variables, calculation of the present values, dynamic programming calculations with the objective of defining the maximum revenues, the programming development using MatLab software and validation of model. The simulations were performed using the discount rates based on the IPCA, CDI, IGP-M, Selic and Selic targets. The use of Monte Carlo method allowed the generation of a series of policies for each simulation, being analysed statistically as a way to verify the one that would best represent the replacement policy and consequently defined the economic useful life of the good. The model was applied to a vertical milling centre and showed flexibility in the information of the input data when using the programming in the software MatLab. It was observed that in addition to generating a range of possibilities the PD+MMC model can assist the decision maker regarding the strategy to be used in the replacement of machine. The PD + MMC calculations, for a 15-year planning horizon, using the five discount rates, provided replacement policies with economic life estimated 3-year economic life for the CDI, Selic and Selic and Useful life over 15 years for the IPCA and IGP-M rates. The PD+MMC calculations for a planning horizon of 15 years, using the five discount rates, provided replacement policies with three years useful life estimate for CDI, Selic and target Selic rates and for the IPCA and plus than fifteen years useful life for IPCA and IGP-M rates. By means of the statistical analyzes it was possible to define that the substitution policy that presented the highest reliability was the one that used the IPCA / IBGE, which generated the highest revenue and the longest useful life of the machine, over 16 years, presenting a significance of 77, 56% for policy frequency.

Uma revisão dos algoritmos e conjuntos de instâncias presentes na literatura do Problema da Mochila com Repetições (PMR) é apresentada nessa dissertação de mestrado. Os algoritmos e conjuntos de instâncias usados são brevemente descritos nesse trabalho, afim de que o leitor tenha base para entender as discussões. Algumas propriedades bem conhecidas e específicas do PMR, como a dominância e a periodicidade, são explicadas com detalhes. O PMR é também superficialmente estudado no contexto de problemas de avaliação gerados pela abordagem de geração de colunas aplicada na relaxação contínua do Bin Packing Problem (BPP) e o Cutting Stock Problem (CSP). Múltiplos experimentos computacionais e comparações são realizadas. Para os conjuntos de instâncias artificiais mais recentes da literatura, um simples algoritmo de programação dinâmica, e uma variante do mesmo, parecem superar o desempenho do resto dos algoritmos, incluindo aquele que era estado-da-arte. O modo que relações de dominância é aplicado por esses algoritmos de programação dinâmica têm algumas implicações para as relações de dominância previamente estudadas na literatura. O autor dessa dissertação defende a tese de que a escolha dos conjuntos de instâncias artificiais definiu o que foi considerado o melhor algoritmo nos trabalhos anteriores. O autor dessa dissertação disponibilizou publicamente todos os códigos e conjuntos de instâncias referenciados nesse trabalho. / A review of the algorithms and datasets in the literature of the Unbounded Knapsack Problem (UKP) is presented in this master's thesis. The algorithms and datasets used are brie y described in this work to provide the reader with basis for understanding the discussions. Some well-known UKP-speci c properties, such as dominance and periodicity, are described. The UKP is also super cially studied in the context of pricing problems generated by the column generation approach applied to the continuous relaxation of the Bin Packing Problem (BPP) and Cutting Stock Problem (CSP). Multiple computational experiments and comparisons are performed. For the most recent arti cial datasets in the literature, a simple dynamic programming algorithm, and its variant, seems to outperform the remaining algorithms, including the previous state-of-the-art algorithm. The way dominance is applied by these dynamic programming algorithms has some implications for the dominance relations previously studied in the literature. In this master's thesis we defend that choosing sets of arti cial instances has de ned what was considered the best algorithm in previous works. We made available all codes and datasets referenced in this master's thesis.

O estudo da substituição de bens de capital proporciona a empresa uma visão sobre a vida útil dos seus bens e oportuniza o planejamento para efetuar, dentro de um tempo ótimo, a troca do bem atual por um substituto que possa oferecer vantagens no que diz respeito a custos de operação e manutenção, sendo possível obter com isso a maximização das receitas. Esta dissertação propõe um modelo para a avaliação da vida útil econômica de máquinas e equipamentos fazendo uso da programação dinâmica (PD) com a geração de números aleatórios por meio do método de Monte Carlo (MMC). O modelo contempla a definição das variáveis que serão utilizadas, a aplicação do método de Monte Carlo às variáveis, o cálculo dos valores presentes, os cálculos da programação dinâmica com o objetivo de definir a máxima receita, o desenvolvimento da programação com o uso do software MatLab e a validação do modelo. As simulações foram realizadas utilizando as taxas de desconto baseadas no IPCA, CDI, IGP-M, Selic e meta Selic. A utilização do método de Monte Carlo possibilitou a geração de uma série de políticas para cada simulação, sendo estas analisadas estatisticamente como forma de verificar aquela que melhor representaria a política de substituição e consequentemente definisse a vida útil econômica do bem. O modelo foi aplicado a um centro de usinagem vertical e demonstrou flexibilidade na informação dos dados de entrada ao se utilizar a programação no software MatLab. Observou-se que além de gerar uma gama de possibilidades o modelo PD+MMC pode auxiliar o tomador de decisão quanto a estratégia a ser utilizada na substituição da máquina. Os cálculos efetuados por meio do modelo PD+MMC, para um horizonte de planejamento de 15 anos, utilizando as cinco taxas de desconto, forneceram políticas de substituição com estimativas de vida útil econômica de 3 anos para as taxas CDI, Selic e meta Selic e vida útil superior a 15 anos para as taxas IPCA e IGP-M. Por meio das análises estatísticas foi possível definir que a política de substituição que apresentou maior confiabilidade foi a que utilizou o IPCA/IBGE, a qual gerou a maior receita e a maior vida útil da máquina, superior a 16 anos, apresentando significância de 77,56% para a frequência de políticas. / The replacement study of capital goods provides to the company an overview about the useful life of its assets and provides planning for effecting, within an optimal time, the exchange of the present good by a substitute that may offer advantages with respect to Costs of operation and maintenance, being possible to obtain the maximization of revenues. This dissertation proposes a model for evaluation of economic useful life of machines and equipment making use of dynamic programming (PD) with the generation of random numbers by the Monte Carlo method (MMC). The model includes variables definition that will be used, the application of the Monte Carlo method to the variables, calculation of the present values, dynamic programming calculations with the objective of defining the maximum revenues, the programming development using MatLab software and validation of model. The simulations were performed using the discount rates based on the IPCA, CDI, IGP-M, Selic and Selic targets. The use of Monte Carlo method allowed the generation of a series of policies for each simulation, being analysed statistically as a way to verify the one that would best represent the replacement policy and consequently defined the economic useful life of the good. The model was applied to a vertical milling centre and showed flexibility in the information of the input data when using the programming in the software MatLab. It was observed that in addition to generating a range of possibilities the PD+MMC model can assist the decision maker regarding the strategy to be used in the replacement of machine. The PD + MMC calculations, for a 15-year planning horizon, using the five discount rates, provided replacement policies with economic life estimated 3-year economic life for the CDI, Selic and Selic and Useful life over 15 years for the IPCA and IGP-M rates. The PD+MMC calculations for a planning horizon of 15 years, using the five discount rates, provided replacement policies with three years useful life estimate for CDI, Selic and target Selic rates and for the IPCA and plus than fifteen years useful life for IPCA and IGP-M rates. By means of the statistical analyzes it was possible to define that the substitution policy that presented the highest reliability was the one that used the IPCA / IBGE, which generated the highest revenue and the longest useful life of the machine, over 16 years, presenting a significance of 77, 56% for policy frequency.

Orientador: João Bosco Ribeiro do Val / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-07T09:08:47Z (GMT). No. of bitstreams: 1 Arruda_EdilsonFernandesde_D.pdf: 7031418 bytes, checksum: 5dc90e2d3823b0e6bcf659159d183007 (MD5) Previous issue date: 2006 / Resumo: Apresenta-se um modelo de controle por intervenções para o problema de produção e estoque de vários itens, com diversos estágios de produção. Este problema pode ser solucionado via programação dinâmica discreta (PD) por um operador de custo descontado. Para contornar a dificuldade de obtenção da solução ótima via PD ao se considerar um número razoável de classes de itens e suas etapas de produção, esta tese desenvolve-se em duas linhas. A primeira delas consiste em tomar uma noção de estabilidade estocástica no sentido Foster-Lyapunov para caracterizar a família de soluções candidatas a ótima, originando uma classe de políticas que geram um subconjunto de estados que são recorrentes positivos. Dessa forma, é possível propor políticas sub-ótimas que sejam estáveis, e cuja consideração de otimalidade possa ser desenvolvida apenas no subconjunto de estados recorrentes, simplificando a tarefa da PD e focando nos estados mais freqüentados no longo prazo. A segunda linha de abordagem consiste em desenvolver técnicas de PD aproximada para o problema, através de uma arquitetura de aproximação fixa aplicada a um subconjunto amostra do espaço de estados. Um avanço analítico é alcançado por observar como uma arquitetura de aproximação pode capturar adequadamente a função valor do problema, vista como uma projeção da função valor na arquitetura. Condições para que um algoritmo de PD aproximada convirja para essa projeção são obtidas. Essas condições são independentes da arquitetura utilizada. Um algoritmo derivado dessa análise é proposto, a partir do monitoramento da variação de passos sucessivos / Abstract: We propose an intervention control model for a multi-product, multi-stage, single machine production and storage problem. The optimal policy is obtained by means of discrete dynamic programming (DP), through a discounted cost contraction mapping. In order to overcome the difficulty of obtaining the optimal solution for problems with a reasonable number of products and production stages, we take two different approaches. The first one consists in using a notion of stochastic stability in the Foster-Lyapunov sense to characterize the candidate policies, thus originating a class of policies that induce a subset of positive recurrent states. Therefore, one can propose suboptimal policies that are stable and seek optimality only in the subset of recurrent states, in such a way that simplifies the DP task and focuses on the states which are visited more frequently in the long run. The second approach consists in developing approximate dynamic programming techniques for the problem, by means of a fixed approximation architecture applied to a sample subset of the state space. A novel result is obtained by observing how an approximation architecture can adequately capture the value function of the problem, which is viewed as a projection of the value function into the architecture. We obtain conditions for an approximate DP algorithm to converge to this projection. These conditions are architecture independent. An algorithm derived from this analysis is proposed that monitors the variation between successive iterates / Doutorado / Automação e Controle / Doutor em Engenharia Elétrica

Orientador: João Bosco Ribeiro do Val / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-16T02:55:02Z (GMT). No. of bitstreams: 1 Souto_RafaelFontes_M.pdf: 470367 bytes, checksum: 516cc5b88625a7d2e5142b69233188f5 (MD5) Previous issue date: 2010 / Resumo: Esta dissertação apresenta uma caracterização para sistemas estocásticos em tempo contínuo em que a variação da ação de controle aumenta a incerteza sobre o estado. Este tipo de sistema pode ser aplicado em diversas áreas da ciência e da engenharia, haja vista sua capacidade de modelar sistemas estocásticos complexos, cujas dinâmicas não são completamente conhecidas. Processos de difusão controlada de Itô são usados para descrever a trajetória do estado, e a otimização é realizada por meio do método da programação dinâmica, sendo, portanto, necessária a resolução da equação de Hamilton-Jacobi-Bellman. Adicionalmente, a utilização de ferramentas da análise de funções não suaves indicou a existência de uma região no espaço de estados onde a ação ótima de controle consiste na manutenção do controle que tem sido aplicado ao sistema, seja ele qual for. Intuitivamente, este resultado está de acordo com a natureza cautelosa do controle de sistemas subdeterminados. Finalmente, estudou-se analiticamente o caso particular de um sistema com custo quadrático. Este estudo revelou que a técnica desenvolvida permite o cálculo da solução ótima de maneira simples e eficaz para comportamentos assintóticos do sistema. Essa peculiaridade da solução vem de auxílio à obtenção da solução completa do problema via aproximações numéricas / Abstract: This dissertation presents a framework for continuous-time stochastic systems in which the control variations increase the state uncertainty. This type of system can be applied in several areas of science and engineering, due to its hability of modelling complex stochastic systems, for which the dynamics are not completely known. Controlled Itô diffusion processes are used in order to describe the state path, and the optimization was achieved by the dynamic programming method, so it was necessary to solve the Hamilton-Jacobi-Bellman equation. In addition, tools from nonsmooth analysis indicated the existence of a region in the state space in which the optimal control action is characterized by no variation, no matter the previous control were. Intuitively, this result is expected from the cautionary nature of controlling underdetermined systems. Finally, it was analytically studied the particular case of a system with quadratic running costs. This study revealed that the technique developed allows the computation of the optimal solution in a simple and effective way for asymptotic behavior of the system. This feature of the solution comes in hand to obtain the complete solution of the problem by means of numerical approximations / Mestrado / Automação / Mestre em Engenharia Elétrica

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-09-12T20:15:40Z No. of bitstreams: 1 taianyabreusoares.pdf: 2853882 bytes, checksum: 995c5563db2de673ae46d3577d5bc5a5 (MD5) / Approved for entry into archive by Diamantino Mayra (mayra.diamantino@ufjf.edu.br) on 2016-09-13T12:32:05Z (GMT) No. of bitstreams: 1 taianyabreusoares.pdf: 2853882 bytes, checksum: 995c5563db2de673ae46d3577d5bc5a5 (MD5) / Made available in DSpace on 2016-09-13T12:32:05Z (GMT). No. of bitstreams: 1 taianyabreusoares.pdf: 2853882 bytes, checksum: 995c5563db2de673ae46d3577d5bc5a5 (MD5) Previous issue date: 2011-02-07 / As principais razões para realizar uma abertura de capital são que as ofertas de ações são uma opção de financiamento mais barata para algumas empresas (dados seus atributos), a governança corporativa trazida pela estrutruta de propriedade pública minimiza os conflitos de agência, a transparência e a boa imagem da empresa (comportamento estratégico) aumentam o valor da empresa no mercado e a reestruturação societária pode gerar mais liquidez para a empresa. Entretanto, para algumas empresas de capital fechado, a questão não é se ela deve abrir ou não o capital, mas sim quando, ou seja, qual o momento mais apropriado (timing) para realizar o IPO. Nesse contexto, o presente trabalho teve por objetivo adaptar, para o caso brasileiro, o modelo de timing de IPO desenvolvido por Draho (2000), que utiliza a teoria das opções reais como metodologia para se determinar o timing ótimo da abertura de capitais. Para tanto, foram analisadas oito empresas do setor de energia (CPFL, EDP, Cosan, Brasil Ecodiesel, São Martinho, Açúcar Guarani, MPX e OGX) que, durante o período 2000-2009, realizaram a sua oferta pública primária. Como resultado, encontrou-se que todas as empresas estudadas anteciparam o timing da sua oferta e, assim, foi realizada uma análise sobre as características das ofertas públicas primárias das empresas com o objetivo de identificar potenciais determinantes de tal antecipação. Observou-se, como característica comum, a presença de capital de risco na estrutura de capital de todas as empresas e de muitos investidores otimistas (investidores externos à empresa, segundo o modelo de Bouis, 2003) interessados nos IPOs das empresas. Adicionalmente, tem-se que o período da amostra (anos de valorização da bolsa de valores brasileira, que antecederam a crise subprime deflagrada em 2008) pode ter também contribuído para tal resultado. / The main reasons addressed to warrant the opening of capital are the initial public offerings (IPO) are cheaper financing option for some companies (according to their attributes), the corporate governance brought by public-owned minimizing agency conflicts, transparency and good image of the company (strategic behavior) increases the value of their market and corporate restructuring can generate more liquidity for the company. However, for some private companies it is not a question of why go public, but rather what the most appropriate time to conduct the IPO. In this context, this study aimed to adapt to the Brazilian case, the model of the IPO timing developed by Draho (2000), which uses the real options theory as a method to determine the optimal timing for an IPO. For this, were analyzed eight Brazilian energy companies (CPFL, EDP, Cosan, Brazil Ecodiesel, St. Martin, Açúcar Guarani, MPX and OGX) that held their primary offering during the period 2000-2009. As a result, we found that all the companies studied had anticipated their timing of IPO and thus, an analysis over characteristics of primary public offerings of companies was performed with the aim of identifying the main reasons for the anticipation. It was observed as common feature the presence of venture capital in the capital structure of all companies and many optimistic investors (investors outside the company, according to the model Bouis, 2003) interested in IPOs of companies. Additionally, the sample period (year of valuation of the Brazilian stock exchange, which preceded the subprime crisis erupted in 2008) may have also contributed to this result.

Manually creating test cases is time consuming and error prone. Search-based software testing (SBST) can help automate this process and thus to reduce time and effort and increase quality by automatically generating relevant test cases. Previous research have mainly focused on static programming languages with simple test data inputs such as numbers. In this work we present an approach for search-based software testing for dynamic programming languages that can generate test scenarios and both simple and more complex test data. This approach is implemented as a tool in and for the dynamic programming language Ruby. It uses an evolutionary algorithm to search for tests that gives structural code coverage. We have evaluated the system in an experiment on a number of code examples that differ in complexity and the type of input data they require. We compare our system with the results obtained by a random test case generator. The experiment shows, that the presented approach can compete with random testing and, for many situations, quicker finds tests and data that gives a higher structural code coverage.

There are a lot more roads being built periodically in most of the countries with the advancement of modern society. In order to promote the overall traffic flow quality within different cities, city traffic management has been playing a more and more essential role during the last few decades. In recent years, a significantly increasing attention has been paid to the management of traffic flow in major cities all over the world. In this thesis, we develop a stochastic dynamic model for urban traffic along with physical constraints characteristic of intersections equipped with traffic light. We assume that the incoming traffic to each stream in an intersection is amenable to the Poisson random process with variable intensity (mean). We introduce expressions for traffic throughput, congestion as well as operator's waiting time for the typical intersection in a city and hereafter define an appropriate objective functional. Afterwards, we formulate an optimization problem and propose the sequential (or recursive) algorithm based on the principle of optimality (dynamic programming) due to Bellman. The solution if implemented is expected to improve throughput, reduce congestion, and promote driver's satisfaction. Because the dynamic programming method is computationally quite intensive, we consider the scenario that one unit traffic stream stands for a specific number of vehicles which actually depends on the volume of traffic flow through the intersection. The system is simulated with inputs described by several distinct nonhomogeneous Poisson processes. For example, we apply the typical traffic arrival rate in Canada with morning peak hour at around 7:30 AM and afternoon peak hour at around 4:30 PM whilst it is also applied with morning rush hour at about 8:00 AM and afternoon rush hour at about 6:00 PM like in China. In the meanwhile, we also present a group of numerical results for the traffic arrival rates that have shorter morning peak-hour period but longer afternoon rush hour period. This may occasionally happen when there are some social activities or big events in the afternoon. In addition, another series of experiments are carried out to illustrate the feasibility of the proposed dynamic model based on the traffic arrival rates with only one peak-hour throughout the whole day. The system is simulated with a series of experiments and the optimization problem is solved by dynamic programming based on the proposed algorithm which gives us the optimal feedback control law. More specifically, the results show that both the optimal traffic light timing allocated for each stream and the congestion broadcast level (CBL) of each road segment during each time segment are found. Accordingly, the corresponding optimal cost can be found for any given initial condition. It is reasonably believed that this stochastic dynamic model would be potentially applicable for real time adaptive traffic control system.

Change-point detection aims to reveal sudden changes in sequences of data. Special attention has been paid to the detection of abrupt level shifts, and applications of such techniques can be found in a great variety of fields, such as monitoring of climate change, examination of gene expressions and quality control in the manufacturing industry. In this work, we compared the performance of two methods representing frequentist and Bayesian approaches, respectively. The frequentist approach involved a preliminary search for level shifts using a tree algorithm followed by a dynamic programming algorithm for optimizing the locations and sizes of the level shifts. The Bayesian approach involved an MCMC (Markov chain Monte Carlo) implementation of a method originally proposed by Barry and Hartigan. The two approaches were implemented in R and extensive simulations were carried out to assess both their computational efficiency and ability to detect abrupt level shifts. Our study showed that the overall performance regarding the estimated location and size of change-points was comparable for the Bayesian and frequentist approach. However, the Bayesian approach performed better when the number of change-points was small; whereas the frequentist became stronger when the change-point proportion increased. The latter method was also better at detecting simultaneous change-points in vector time series. Theoretically, the Bayesian approach has a lower computational complexity than the frequentist approach, but suitable settings for the combined tree and dynamic programming can greatly reduce the processing time.

Updates are a natural part of the life cycle of an application. The traditional way of updating an application by stopping it, replacing it with the new version and restarting it is lacking in many ways. There have been previous research in the field of dynamic software updates (DSU) that attempt to salvage this problem by updating the app while running. Most of the previous research have focused on static languages like C and Java, research with dynamic languages have been lacking. This thesis takes advantage of the dynamic features of JavaScript in order to allow for dynamic updates of applications for mobile devices. The solution is implemented and used to answer questions about how correctness can be ensured and what state transfer needs to be manually written by a programmer. The conclusion is that most failures that occur as the result of an update and is in need of a manually written state transfer can be put into one of three categories. To verify correctness of an update tests for these types of failures should be performed.