77 resultados para Otimização matematica


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The present essay shows strategies of improvement in a well succeded evolutionary metaheuristic to solve the Asymmetric Traveling Salesman Problem. Such steps consist in a Memetic Algorithm projected mainly to this problem. Basically this improvement applied optimizing techniques known as Path-Relinking and Vocabulary Building. Furthermore, this last one has being used in two different ways, in order to evaluate the effects of the improvement on the evolutionary metaheuristic. These methods were implemented in C++ code and the experiments were done under instances at TSPLIB library, being possible to observe that the procedures purposed reached success on the tests done

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In Survival Analysis, long duration models allow for the estimation of the healing fraction, which represents a portion of the population immune to the event of interest. Here we address classical and Bayesian estimation based on mixture models and promotion time models, using different distributions (exponential, Weibull and Pareto) to model failure time. The database used to illustrate the implementations is described in Kersey et al. (1987) and it consists of a group of leukemia patients who underwent a certain type of transplant. The specific implementations used were numeric optimization by BFGS as implemented in R (base::optim), Laplace approximation (own implementation) and Gibbs sampling as implemented in Winbugs. We describe the main features of the models used, the estimation methods and the computational aspects. We also discuss how different prior information can affect the Bayesian estimates

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Recently, capuchin monkeys (Cebus spp.) inhabitants of dry environments and with restriction of fleshy fruits, have been the subject of several studies regarding the use of instruments. During behaviour of using stones to crack open nuts there is evidence of selection of more effective hammers, as well as selection of anvils related to reducing the risk of predation. The aim of this study was to determine whether two groups of capuchin monkeys (C.flavius and and C.libidinosus) inhabitants of the Caatinga of Rio Grande do Norte make choice of hammers and anvils. The record of weight and location of stones indicated active choices of with what (choice of hammers) and where (selection of anvils) to crack open encapsulated seeds. The choice of hammers to break nuts depended on the type and degree of ripeness seed. Thus, smaller seeds were smashed with lighter hammers and larger seeds with heavier hammers. Still, C. flavius was the only species that presented a refinement in the choice of hammers that depended on the ripeness of seeds. For both species of capuchin monkeys studied, the nut-crack sites were not spread in accordance with the spatial distribution of seed-producing species, suggesting that the capuchin monkeys promote active choice of anvils. Thus, in environments with more escape routes through the trees, the nut-crack sites were found further apart than in regions that had less chance of escape through the trees. Also, there was a difference in the spacing of the anvils to depend on the type of seed: sites used to crack larger and more caloric seeds were found farther apart than the sites used to crack smaller and less caloric seeds, suggesting a pattern of avoiding direct competition. We conclude that the capuchin monkeys maximize energy savings and reduced risk of predation and the costs of food competition during the behaviour of using stones to crack open nuts

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Cutting fluids are lubricants used in metal-mechanical industries. Their complex composition varies according to the type of operation carried out, also depending on the metals under treatment or investigation. Due to the high amount of mineral oil produced in Northeastern Brazil, we have detected the need to better use this class of material. In this work, two novel formulations have been tested, both based on naphthenic mineral oil and additives, such as: an emulsifying agent (A), an anticorrosion agent (B), a biocide (C) and an antifoam agent (D). Each formulation was prepared by mixing the additives in the mineral oil at a 700-rpm stirring velocity for 10 min, at 25°C, employing a 24 factorial planning. The formulations were characterized by means of density, total acid number (TAN), viscosity, flash point and anticorrosion activity. In a subsequent study, oil-in-water emulsions were prepared from these novel formulations. The emulsions were analyzed in terms of stability, corrosion degree, percentage of foam formation, conductivity, accelerated stability and particle size. The samples were appropriately labeled, and, in special, two of them were selected for featuring emulsion properties which were closer to those of the standards chosen as references (commercial cutting oils). Investigations were undertaken on the ability of NaCl and CaCl2 to destabilize the emulsions, at concentrations of 2%, 5% and 10%, at an 800-rpm stirring velocity for 5 min and temperatures of 25º, 40º, 50º and 60ºC. The recovered oils were chemically altered by reincorporating the same additives used in the original formulations, followed by preparation of emulsions with the same concentrations as those of the initial ones. The purpose was to assess the possibility of reusing the recovered oil. The effluents generated during the emulsion destabilization step were characterized via turbidity index, contents of oil and grease, pH, and contents of anions and cations, observing compliance with the parameters established by the current environmental legislation (Brazil s CONAMA 357/05 resolution). It could be concluded that the formulations presented excellent physicochemical properties as compared to commercial cutting fluids, showing that the quality of the newly-prepared fluids is superior to that of the formulations available in the market, enabling technically and environmentally-safe applications

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This work aims to detect polycyclic aromatic hydrocarbons (PAHs) through optimized analytical techniques, such as gas chromatography with flame-ionisation detector (CGFID), gas chromatography coupled to mass spectrometry (CGMS), Fluorescence Spectroscopy of Molecular and Purpot of oils and greases (POG). Apply to chemometrics, Factorial Planning 23, in the preparation of samples by liquid-liquid extraction. The sample preparation was used for liquid-liquid extraction and factors in this sample was used for the application of factorial planning 23, such as the use of ultrasound, solvents (dichloromethane, hexane and chloroform) and ratio of solvent / synthetic sample. These factors were assigned two types of levels: positive and negative. It was used to form the cube to better analyze the answers. The responses of the eight combinations were obtained in reading the spectrofluorimetric. The optimization of equipment were used, and they served in the HPA's identification of the samples collected in Rio Potengi. The optimization of the equipment was observed every 16's and PAH in the samples was found that the HPA's came from contamination of the Rio Potengi. The contamination comes through organic household waste, hospital waste, and among other contamination that comes from industries that are installed around the River The factorial design of high validity, it was observed a more effective sample preparation. The factorial design of liquid-liquid extraction showed a way to spend less solvent in less time using an ideal solvent, but also a way to extract more analyte from the matrix itself is water. In planning a smaller form factor extraction was the use of ultrasound, the ratio 1:3 corresponding to a solvent and sample 3 and the best solvent was dichloromethane who presented a viable extraction, not discarding the possibility of using also the hexane. The chloroform and may be toxic not had a good extraction

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Different compositions of Ni0,5-xCuxZn0,5Fe2O4 and Ni0,5-xCoxZn0,5Fe2O4 0 ≤ x ≤ 0.3 were synthesized ferrite y the citrate precursor method. The stoichiometric compositions were calcined in air at 350°C and then pressed into pellets and toroids. The pressed samples were sintered at temperatures of 1000, 1050 and 1100°C/3h in air control at the speed of heating and cooling. The calcined powders were characterized by XRD, TGA / DTG, FTIR, SEM and vibrating sample magnetometry (VSM) and the sintered samples by XRD, SEM, MAV, density and measurements of permeability and magnetic losses. There was pure phase formation ferrimagnetism applied at all temperatures except for A-I composition at all sintering temperatures and A-II only at a temperature of 1100°C. Crystallite sizes were obtained by Rietveld analysis, nanometer size from 11 to 20 nm for the calcined powders. For SEM, the sintered samples showed grain size between 1 and 10 micrometers. Bulk density (ρ) of sintered material presented to the Families almost linear behavior with increasing temperature and a tendency to decrease with increasing concentration of copper, different behavior of the B Family, where the increase in temperature decreased the density. The magnetic measurements revealed the powder characteristics of a soft ferrimagnetic material. Two processes of magnetization were considered, the superparamagnetism at low temperatures (350°C) and the formation of magnetic domains at higher temperatures. Obtaining the best parameters for P and B-II magnetic ferrites at high temperatures. The sintered material at 1000°C showed a relative permeability (μ) from 50 to 800 for the A Family and from 10 to 600 for the B Family. The samples sintered at 1100°C, B Family showed a variation from 10 to 1000 and the magnetic loss (tan δ) of A and B Families, around of 1. The frequency response of the toroidal core is in the range of 0.3 kHz. Several factors contribute to the behavior of microstructure considering the quantities μ and tan δ, such as the grain size, inter-and intragranular porosity, amount of grain boundary and the aspects of the dynamics of domain walls at high frequencies.

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Topics of research related to energy and environment have significantly grown in recent years, with the need of its own energy as hydrogen. More particularly, numerous researches have been focused on hydrogen as energy vector. The main portion of hydrogen is presently obtained by reforming of methane or light hydrocarbons (steam, oxy, dry or auto reforming). During the methane steam reforming process the formation of CO2 undesirable (the main contributor to the greenhouse effect) is observed. Thus, an oxide material (sorbent) can be used to capture the CO2 generated during the process and simultaneously shifting the equilibrium of water gas shift towards thermodynamically more favorable production of pure hydrogen. The aim of this study is to develop a material with dual function (catalyst/sorbent) in the reaction of steam reforming of methane. CaO is well known as CO2 sorbent due to its high efficiency in reactions of carbonation and easy regeneration through calcination. However the kinetic of carbonation decreases quickly with time and carbonation/calcination cycles. A calcium aluminate (Ca12Al14O33) should be used to avoid sintering and increase the stability of CaO sorbents for several cycles. Nickel, the industrial catalyst choice for steam reforming has been added to the support from different manners. These bi-functional materials (sorbent/catalyst) in different molar ratios CaO.Ca12Al14O33 (48:52, 65:35, 75:25, 90:10) were prepared by different synthesis methodologies, among them, especially the method of microwave assisted self-combustion. Synthesis, structure and catalytic performances of Ni- CaO.Ca12Al14O33 synthesized by the novel method (microwave assisted selfcombustion) proposed in this work has not being reported yet in literature. The results indicate that CO2 capture time depends both on the CaO excess and on operating conditions (eg., temperature and H2O/CH4 ratio). To be efficient for CO2 sorption, temperature of steam reforming needs to be lower than 700 °C. An optimized percentage corresponding to 75% of CaO and a ratio H2O/CH4 = 1 provides the most promising results since a smaller amount of water avoids competition between water and CO2 to form carbonate and hydroxide. If this competition is most effective (H2O/CH4 = 3) and would have a smaller amount of CaO available for absorption possibly due to the formation of Ca(OH)2. Therefore, the capture time was higher (16h) for the ratio H2O/CH4 = 1 than H2O/CH4 = 3 (7h) using as catalyst one prepared by impregnating the support obtained by microwave assisted self-combustion. Therefore, it was demonstrated that, with these catalysts, the CO2 sorption on CaO modifies the balance of the water gas-shift reaction. Consequently, steam reforming of CH4 is optimized, producing pure H2, complete conversion of methane and negligible concentration of CO2 and CO during the time of capture even at low temperature (650 °C). This validates the concept of the sorption of CO2 together with methane steam reforming

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Traditional applications of feature selection in areas such as data mining, machine learning and pattern recognition aim to improve the accuracy and to reduce the computational cost of the model. It is done through the removal of redundant, irrelevant or noisy data, finding a representative subset of data that reduces its dimensionality without loss of performance. With the development of research in ensemble of classifiers and the verification that this type of model has better performance than the individual models, if the base classifiers are diverse, comes a new field of application to the research of feature selection. In this new field, it is desired to find diverse subsets of features for the construction of base classifiers for the ensemble systems. This work proposes an approach that maximizes the diversity of the ensembles by selecting subsets of features using a model independent of the learning algorithm and with low computational cost. This is done using bio-inspired metaheuristics with evaluation filter-based criteria

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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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This work seeks to propose and evaluate a change to the Ant Colony Optimization based on the results of experiments performed on the problem of Selective Ride Robot (PRS, a new problem, also proposed in this paper. Four metaheuristics are implemented, GRASP, VNS and two versions of Ant Colony Optimization, and their results are analyzed by running the algorithms over 32 instances created during this work. The metaheuristics also have their results compared to an exact approach. The results show that the algorithm implemented using the GRASP metaheuristic show good results. The version of the multicolony ant colony algorithm, proposed and evaluated in this work, shows the best results

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Committees of classifiers may be used to improve the accuracy of classification systems, in other words, different classifiers used to solve the same problem can be combined for creating a system of greater accuracy, called committees of classifiers. To that this to succeed is necessary that the classifiers make mistakes on different objects of the problem so that the errors of a classifier are ignored by the others correct classifiers when applying the method of combination of the committee. The characteristic of classifiers of err on different objects is called diversity. However, most measures of diversity could not describe this importance. Recently, were proposed two measures of the diversity (good and bad diversity) with the aim of helping to generate more accurate committees. This paper performs an experimental analysis of these measures applied directly on the building of the committees of classifiers. The method of construction adopted is modeled as a search problem by the set of characteristics of the databases of the problem and the best set of committee members in order to find the committee of classifiers to produce the most accurate classification. This problem is solved by metaheuristic optimization techniques, in their mono and multi-objective versions. Analyzes are performed to verify if use or add the measures of good diversity and bad diversity in the optimization objectives creates more accurate committees. Thus, the contribution of this study is to determine whether the measures of good diversity and bad diversity can be used in mono-objective and multi-objective optimization techniques as optimization objectives for building committees of classifiers more accurate than those built by the same process, but using only the accuracy classification as objective of optimization

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Este trabalho aborda o problema de otimização em braquiterapia de alta taxa de dose no tratamento de pacientes com câncer, com vistas à definição do conjunto de tempos de parada. A técnica de solução adotada foi a Transgenética Computacional apoiada pelo método L-BFGS. O algoritmo desenvolvido foi empregado para gerar soluções não denominadas cujas distribuições de dose fossem capazes de eiminar o câncer e ao mesmo tempo preservar as regiões normais

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This paper proposes a new control chart to monitor a process mean employing a combined npx-X control chart. Basically the procedure consists of splitting the sample of size n into two sub-samples n1 and n2 determined by an optimization search. The sampling occur in two-stages. In the first stage the units of the sub-sample n1 are evaluated by attributes and plotted in npx control chart. If this chart signs then units of second sub-sample are measured and the monitored statistic plotted in X control chart (second stage). If both control charts sign then the process is stopped for adjustment. The possibility of non-inspection in all n items may promote a reduction not only in the cost but also the time spent to examine the sampled items. Performances of the current proposal, individual X and npx control charts are compared. In this study the proposed procedure presents many competitive options for the X control chart for a sample size n and a shift from the target mean. The average time to sign (ATS) of the current proposal lower than the values calculated from an individual X control chart points out that the combined control chart is an efficient tool in monitoring process mean.

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