854 resultados para Heuristic optimization


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In this paper, the use of differential evolution ( DE), a global search technique inspired by evolutionary theory, to find the parameters that are required to achieve optimum dynamic response of parallel operation of inverters with no interconnection among the controllers is proposed. Basically, in order to reach such a goal, the system is modeled in a certain way that the slopes of P-omega and Q-V curves are the parameters to be tuned. Such parameters, when properly tuned, result in system's eigenvalues located in positions that assure the system's stability and oscillation-free dynamic response with minimum settling time. This paper describes the modeling approach and provides an overview of the motivation for the optimization and a description of the DE technique. Simulation and experimental results are also presented, and they show the viability of the proposed method.

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Neste trabalho é analisada a aplicação de algoritmos heurísticos para o Modelo Híbrido Linear - Hybrid Linear Model (HLM) - no problema de planejamento da expansão de sistemas de transmissão. O HLM é um modelo relaxado que ainda não foi suficientemente explorado. Assim, é realizada uma análise das características do modelo matemático e das técnicas de solução que podem ser usadas para resolver este tipo de modelo. O trabalho analisa em detalhes um algoritmo heurístico construtivo para o HLM e faz uma extensão da modelagem e da técnica de solução para o planejamento multi-estágio da expansão de sistemas de transmissão. Dentro deste contexto, também é realizada uma avaliação da qualidade das soluções encontradas pelo HLM e as possibilidades de aplicação deste modelo em planejamento de sistemas de transmissão. Finalmente, são apresentados testes com sistemas conhecidos na literatura especializada.

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The Quadratic Minimum Spanning Tree Problem (QMST) is a version of the Minimum Spanning Tree Problem in which, besides the traditional linear costs, there is a quadratic structure of costs. This quadratic structure models interaction effects between pairs of edges. Linear and quadratic costs are added up to constitute the total cost of the spanning tree, which must be minimized. When these interactions are restricted to adjacent edges, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). AQMST and QMST are NP-hard problems that model several problems of transport and distribution networks design. In general, AQMST arises as a more suitable model for real problems. Although, in literature, linear and quadratic costs are added, in real applications, they may be conflicting. In this case, it may be interesting to consider these costs separately. In this sense, Multiobjective Optimization provides a more realistic model for QMST and AQMST. A review of the state-of-the-art, so far, was not able to find papers regarding these problems under a biobjective point of view. Thus, the objective of this Thesis is the development of exact and heuristic algorithms for the Biobjective Adjacent Only Quadratic Spanning Tree Problem (bi-AQST). In order to do so, as theoretical foundation, other NP-hard problems directly related to bi-AQST are discussed: the QMST and AQMST problems. Bracktracking and branch-and-bound exact algorithms are proposed to the target problem of this investigation. The heuristic algorithms developed are: Pareto Local Search, Tabu Search with ejection chain, Transgenetic Algorithm, NSGA-II and a hybridization of the two last-mentioned proposals called NSTA. The proposed algorithms are compared to each other through performance analysis regarding computational experiments with instances adapted from the QMST literature. With regard to exact algorithms, the analysis considers, in particular, the execution time. In case of the heuristic algorithms, besides execution time, the quality of the generated approximation sets is evaluated. Quality indicators are used to assess such information. Appropriate statistical tools are used to measure the performance of exact and heuristic algorithms. Considering the set of instances adopted as well as the criteria of execution time and quality of the generated approximation set, the experiments showed that the Tabu Search with ejection chain approach obtained the best results and the transgenetic algorithm ranked second. The PLS algorithm obtained good quality solutions, but at a very high computational time compared to the other (meta)heuristics, getting the third place. NSTA and NSGA-II algorithms got the last positions

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Due to great difficulty of accurate solution of Combinatorial Optimization Problems, some heuristic methods have been developed and during many years, the analysis of performance of these approaches was not carried through in a systematic way. The proposal of this work is to make a statistical analysis of heuristic approaches to the Traveling Salesman Problem (TSP). The focus of the analysis is to evaluate the performance of each approach in relation to the necessary computational time until the attainment of the optimal solution for one determined instance of the TSP. Survival Analysis, assisted by methods for the hypothesis test of the equality between survival functions was used. The evaluated approaches were divided in three classes: Lin-Kernighan Algorithms, Evolutionary Algorithms and Particle Swarm Optimization. Beyond those approaches, it was enclosed in the analysis, a memetic algorithm (for symmetric and asymmetric TSP instances) that utilizes the Lin-Kernighan heuristics as its local search procedure

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Combinatorial optimization problems have the goal of maximize or minimize functions defined over a finite domain. Metaheuristics are methods designed to find good solutions in this finite domain, sometimes the optimum solution, using a subordinated heuristic, which is modeled for each particular problem. This work presents algorithms based on particle swarm optimization (metaheuristic) applied to combinatorial optimization problems: the Traveling Salesman Problem and the Multicriteria Degree Constrained Minimum Spanning Tree Problem. The first problem optimizes only one objective, while the other problem deals with many objectives. In order to evaluate the performance of the algorithms proposed, they are compared, in terms of the quality of the solutions found, to other approaches

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This work performs an algorithmic study of optimization of a conformal radiotherapy plan treatment. Initially we show: an overview about cancer, radiotherapy and the physics of interaction of ionizing radiation with matery. A proposal for optimization of a plan of treatment in radiotherapy is developed in a systematic way. We show the paradigm of multicriteria problem, the concept of Pareto optimum and Pareto dominance. A generic optimization model for radioterapic treatment is proposed. We construct the input of the model, estimate the dose given by the radiation using the dose matrix, and show the objective function for the model. The complexity of optimization models in radiotherapy treatment is typically NP which justifyis the use of heuristic methods. We propose three distinct methods: MOGA, MOSA e MOTS. The project of these three metaheuristic procedures is shown. For each procedures follows: a brief motivation, the algorithm itself and the method for tuning its parameters. The three method are applied to a concrete case and we confront their performances. Finally it is analyzed for each method: the quality of the Pareto sets, some solutions and the respective Pareto curves

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Humans, as well as some animals are born gifted with the ability to perceive quantities. The needs that came from the evolution of societies and technological resources make the the optimization of such counting methods necessary. Although necessary and useful, there are a lot of diculties in the teaching of such methods.In order to broaden the range of available tools to teach Combinatorial Analysis, a owchart is presented in this work with the goal of helping the students to x the initial concepts of such subject via pratical exercises

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We present the construction of a homogeneous phantom to be used in simulating the scattering and absorption of X-rays by a standard patient chest and skull when irradiated laterally. This phantom consisted of Incite and aluminium plates with their thickness determined by a tomographic exploratory method applied to the anthropomorphic phantom. Using this phantom, an optimized radiographic technique was established for chest and skull of standard sized patient in lateral view. Images generated with this optimized technique demonstrated improved image quality and reduced radiation doses. (c) 2006 Elsevier Ltd. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The objectives of the present study were to optimize the protocol of mouse immunization with Paracoccidioides brasiliensis antigens (Rifkind's protocol) and to test the modulation effect of cyclophosphamide (Cy) on the delayed hypersensitivity response (DHR) of immunized animals. Experiments were carried out using one to four immunizing doses of either crude particulate P. brasiliensis antigen or yeast-cell antigen, followed by DHR test four or seven days after the last immunizing dose. The data demonstrated that an immunizing dose already elicited response; higher DHR indices were obtained with two or three immunizing doses; there were no differences between DHR indices of animals challenged four or seven days after the last dose. Overall the inoculation of two or three doses of the yeast-cell antigen, which is easier to prepare, and DHR test at day 4 simplify the original Rifkind's immunization protocol and shorten the duration of the experiments. The modulation effect of Cy on DHR was assayed with administration of 2.5, 20 and 100 mg/kg weight at seven day intervals starting from day 4 prior to the first immunizing dose. Only the treatment with 2.5 mg Cy increased the DHR indices. Treatment with 100 mg Cy inhibited the DHR, whereas 20 mg Cy did not affect the DHR indices. Results suggest an immunostimulating effect of low dose of Cy on the DHR of mice immunized with P. brasiliensis antigens.

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This study aimed to develop a plate to treat fractures of the mandibular body in dogs and to validate the project using finite elements and biomechanical essays. Mandible prototypes were produced with 10 oblique ventrorostral fractures (favorable) and 10 oblique ventrocaudal fractures (unfavorable). Three groups were established for each fracture type. Osteosynthesis with a pure titanium plate of double-arch geometry and blocked monocortical screws offree angulanon were used. The mechanical resistance of the prototype with unfavorable fracture was lower than that of the fcworable fracture. In both fractures, the deflection increased and the relative stiffness decreased proportionally to the diminishing screw number The finite element analysis validated this plate study, since the maximum tension concentration observed on the plate was lower than the resistance limit tension admitted by the titanium. In conclusion, the double-arch geometry plate fixed with blocked monocortical screws has sufficient resistance to stabilize oblique,fractures, without compromising mandibular dental or neurovascular structures. J Vet Dent 24 (7); 212 - 221, 2010

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Restoring a misaligned tooth with an inadequate contact point is a challenge to the practitioner. In some instances, teeth that could be repositioned and adequately restored are extracted. Thus, the aim of this article was to describe a treatment using orthodontic and prosthetic techniques to restore esthetics and function in a patient with a distally drifted maxillary lateral incisor. The patient's functional and esthetic expectations were successfully met with the outlined treatment.

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This work proposes a mathematical model to aid variety selection and planting quantity of sugarcane in order to reduce crop residues, maximize energy generated by this residue, and satisfy all the supply of the mill. We propose Linear Programming with two objective. The conflict between these objectives allows the use of the Nonzero-sum Game Theory. (C) 2003 Elsevier B.V. Ltd. All rights reserved.

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Cyclodextrin glucanotransferase production from Bacillus clausii E16, a new bacteria isolated from Brazilian soil samples was optimized in shake-flask cultures. A 2 4 full-factorial central composite design was performed to optimize the culture conditions, using a response surface methodology the combined effect among the soluble starch concentration, the peptone concentration, the yeast extract concentration, and the initial pH value of the culture medium was investigated. The optimum concentrations of the components, determined by a 2(4) full-factorial central composite design, were 13.4 g/L soluble starch, 4.9 g/L peptone, 5.9 g/L yeast extract, and initial pH 10.1. Under these optimized conditions, the maximum cyclodextrin glucanotransferase activity was 5.9 U/mL after a 48-h fermentation. This yield was 68% higher than that obtained when the microorganism was cultivated in basal culture medium.