Orientador: Vinícius Amaral Armentano / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-22T22:56:34Z (GMT). No. of bitstreams: 1 Branchini_RodrigoMoretti_D.pdf: 2921053 bytes, checksum: 29694a6f4803c5c222c97cbe95a2b199 (MD5) Previous issue date: 2013 / Resumo: Este trabalho aborda um problema de planejamento tático em empresas de transporte marítimo de carga que coletam e entregam as demandas contratadas por seus clientes. As viagens associadas a estas demandas são obrigatórias, mas a empresa pode também atender a demandas spot associadas com viagens opcionais para aumentar seu lucro durante um horizonte de tempo de médio prazo. O problema de otimização é formulado como um modelo de programação inteira mista que é definido em um grafo orientado em que nós representam viagens obrigatórias e opcionais. As decisões do modelo são determinar o número e tipo de navios que compõem a frota, designar um navio a um conjunto de viagens obrigatórias e opcionais, definir as rotas de cada navio e estipular os tempos de início de atendimento nos portos para cada viagem. Um algoritmo de busca tabu com uma lista de candidatos e um conjunto de soluções de elite são propostos para resolver instâncias do problema. Os resultados computacionais da busca tabu são comparados com as soluções ótimas e sub-ótimas encontradas pelo CPLEX para o modelo de programação inteira mista / Abstract: We address a tactical planning problem faced by many liner shipping companies that have committed contractual voyages while trying to serve optional spot voyages to increase its revenue over the medium-term horizon. The optimization problem is formulated as a mixed integer programming model that is defined on a directed graph whose nodes represent contractual and spot voyages. The decisions include the number and type of vessels deployed the assignment of vessels to contractual and spot voyages and the determination of vessel routes and schedules in order to maximize the profit. A tabu search algorithm with a candidate list and a pool of elite and diverse solutions is proposed in order to solve a set of benchmark instances of the problem. The results obtained by tabu search are compared to optimal and suboptimal solutions yielded by the CPLEX solver to the mixed integer programming formulation of the problem / Doutorado / Automação / Doutor em Engenharia Elétrica

[pt] O aumento do consumo de energia elétrica leva os sistemas de distribuição a operar próximo do seu limite, podendo ocorrer situações de máximo fluxo de potência ativa e reativa nos ramos, ou seja, problemas de estabilidade de tensão. A mudança da topologia da rede permite encontrar uma configuração em que os índices de estabilidade de tensão estão distantes do ponto de máximo carregamento do sistema, reduzir as perdas técnicas e tornar a distribuição de carga nos alimentadores mais uniforme. Contudo, o número de possibilidades de chaveamento cresce com o aumento da dimensão da rede elétrica e a busca pela solução ótima requer esforço computacional elevado. O uso do algoritmo heurístico de Busca Tabu permite direcionar a busca por novas configurações de qualidade, armazenando suas características e proibindo a adição e/ou remoção de atributos por um período, evitando que a busca termine em um valor mínimo (máximo) local. Os resultados das análises em diferentes níveis de carregamento, que representam a operação do sistema radial de distribuição com carga leve, pesada e crítica, mostram que o algoritmo de Busca Tabu adotado neste trabalho consegue maximizar a margem de potência da barra crítica do sistema, levando o ponto de operação original à uma distância maior do ponto de máximo carregamento do sistema, na região normal de operação e minimizando as perdas técnicas. Com isso, evita-se que o sistema opere no ponto de máximo carregamento ou, na pior das hipóteses, na região anormal de operação, onde as ações de controle têm efeito oposto ao esperado. / [en] The increase of the consumption of electric energy takes the distribution systems to operate next to its limits, which might cause situation of maximum active and reactive power flow in the branches, that is, problems of voltage stability. The change of the topology of the network allows to find a configuration where de voltage stability indexes are far from de maximum loading point, improve voltage profile, reduce power losses and load balancing. However, the number of possible switching grows with the dimension of network and searching for optimal solution requires high computational effort. Using Tabu Search heuristics allows guiding the search for new configuration of high quality, being storing its characteristics and forbidding the addition and/or removal of attributes for a period, avoiding that the search finishes in a local minimum (maximum) value. The results in different loading levels, that represent the operation of radial distribution system with normal, weighed and critical load, show that the Tabu Search algorithm maximizes the voltage stability margin, leading the original operation point to a new one that is far from the maximum loading point, in the normal region of operation. With this, it is prevented that the system operates next to the maximum loading point or, in the worse case, in the abnormal region of operation, where the actions of control have opposing effect to the waited one.

In this work, we investigate job-shop problems where limited capacity buffers to store jobs in non-processing periods are present. In such a problem setting, after finishing processing on a machine, a job either directly has to be processed on the following machine or it has to be stored in a prespecified buffer. If the buffer is completely occupied the job may wait on its current machine but blocks this machine for other jobs. Besides a general buffer model,also specific configurations are considered.The key issue to develop fast heuristics for the job-shop problem with buffers is to find a compact representation of solutions. In contrast to the classical job-shop problem,where a solution may be given by the sequences of the jobs on the machines, now also the buffers have to be incorporated in the solution representation. In this work, we propose two solution representations for the job-shop problem with buffers. Furthermore, we investigate whether the given solution representations can be simplified for specific buffer configurations. For the general buffer configuration it is shown that an incorporation of the buffers in the solution representation is necessary, whereas for specific buffer configurations possible simplifications are presented. Based on the given solution representations we develop local search heuristics in the second part of this work. Therefore, the well-known block approach for the classical job-shop problem is generalized to the job-shop problem with specific buffer configurations.

This thesis deals with the problem of vehicle scheduling in public transport. It contains a theoretical introduction to vehicles scheduling and evolutionary algorithms. Vehicle scheduling is analyzed with respect to the bus timetables. Analysis of evolutionary algorithms is done with emphasis on the genetic algorithms and tabu-search method After the theoretical introduction, a memetic algorithm for the given problem is analyzed. Finally, the thesis contains a description of the optimization system implementation and discusses the experiments with the system.

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The purpose of a cost model is to provide designers and decision-makers with accurate cost information to assess and compare multiple alternatives for obtaining the optimal solution and controlling cost. The cost models developed in the design phases are the most important and the most difficult to develop. Therefore it is necessary to identify appropriate cost drivers and employ appropriate modeling techniques to accurately estimate cost for directing designers. The objective of this study is to provide higher predictive accuracy of cost estimation for directing designer in the early design phases of complex products. After a generic cost estimation model is presented and the existing methods for identification of cost drivers and different cost modeling techniques are reviewed, the dissertation first proposes new methodologies to identify and select the cost drivers: Causal-Associated (CA) method and Tabu-Stepwise selection approach. The CA method increases understanding and explanation of the cost analysis and helps avoid missing some cost drivers. The Tabu-Stepwise selection approach is used to select significant cost drivers and eliminate irrelevant cost drivers under nonlinear situation. A case study is created to illustrate their procedure and benefits. The test data show they can improve predictive capacity. Second, this dissertation introduces Tabu-SVR, a nonparametric approach based on support vector regression (SVR) for cost estimation for complex products in the early design phases. Tabu-SVR determines the parameters of SVR via a tabu search algorithm improved by the author. For verification and validation of performance on Tabu-SVR, the five common basic cost characteristics are summarized: accumulation, linear function, power function, step function, and exponential function. Based on these five characteristics and the Flight Optimization Systems (FLOPS) cost module (engine part), seven test data sets are generated to test Tabu-SVR and are used to compare it with other traditional methods (parametric modeling, neural networking and case-based reasoning). The results show Tabu-SVR significantly improves the performance compared to SVR based on empirical study. The radial basis function (RBF) kernel, which is much more robust, often has better performance over linear and polynomial kernel functions. Compared with other traditional cost estimating approaches, Tabu-SVR with RBF kernel function has strong predicable capability and is able to capture nonlinearities and discontinuities along with interactions among cost drivers. The third part of this dissertation focuses on semiparametric cost estimating approaches. Extensive studies are conducted on three semiparametric algorithms based on SVR. Three data sets are produced by combining the aforementioned five common basic cost characteristics. The experiments show Semiparametric Algorithm 1 is the best approach under most situations. It has better cost estimating accuracy over the pure nonparametric approach and the pure parametric approach. The model complexity influences the estimating accuracy for Semiparametric Algorithm 2 and Algorithm 3. If the inexact function forms are used as the parametric component of semiparametric algorithm, they often do not bring any improvement of cost estimating accuracy over the pure nonparametric approach and even worsen the performance. The last part of this dissertation introduces two existing methods for sensitivity analysis to improve the explanation capability of the cost estimating approach based on SVR. These methods are able to show the contribution of cost drivers, to determine the effect of cost drivers, to establish the profiles of cost drivers, and to conduct monotonic analysis. They finally can help designers make trade-off study and answer “what-i” questions. / Ph. D.

In this thesis we investigate the application of two heuristic methods, genetic algorithms and tabu/scatter search, to the optimisation of realistic portfolios. The model is based on the classical mean-variance approach, but enhanced with floor and ceiling constraints, cardinality constraints and nonlinear transaction costs which include a substantial illiquidity premium, and is then applied to a large I 00-stock portfolio. It is shown that genetic algorithms can optimise such portfolios effectively and within reasonable times, without extensive tailoring or fine-tuning of the algorithm. This approach is also flexible in not relying on any assumed or restrictive properties of the model and can easily cope with extensive modifications such as the addition of complex new constraints, discontinuous variables and changes in the objective function. The results indicate that that both floor and ceiling constraints have a substantial negative impact on portfolio performance and their necessity should be examined critically relative to their associated administration and monitoring costs. Another insight is that nonlinear transaction costs which are comparable in magnitude to forecast returns will tend to diversify portfolios; the effect of these costs on portfolio risk is, however, ambiguous, depending on the degree of diversification required for cost reduction. Generally, the number of assets in a portfolio invariably increases as a result of constraints, costs and their combination. The implementation of cardinality constraints is essential for finding the bestperforming portfolio. The ability of the heuristic method to deal with cardinality constraints is one of its most powerful features. / Decision Sciences / M. Sc. (Operations Research)

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