Otimização combinatória para alocação de fontes renováveis em microrredes de corrente contínua

Pós-graduação em Engenharia Elétrica - FEIS

Uma investigação do minos e sua aplicação ao problema de fluxo de potência ótimo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Transmission Expansion Planning Via a Constructive Heuristic Algorithm in Restructured Electricity Industry

The transmission expansion planning problem in modern power systems is a large-scale, mixed-integer, nonlinear and non-convex problem. this paper presents a new mathematical model and a constructive heuristic algorithm (CHA) for solving transmission expansion planning problem under new environment of electricity restructuring. CHA finds an acceptable solution in an iterative process, where in each step a circuit is chosen using a sensitivity index and added to the system. The proposed model consider multiple generation scenarios therefore the methodology finds high quality solution in which it allows the power system operate adequacy in an environment with multiple generators scenarios. Case studies and simulation results using test systems show possibility of using Constructive heuristic algorithm in an open access system.

Metodologia para otimização em subcontratação de serviço de usinagem

Operational Research (OR) is an eminent science to business competitiveness and the capacity of algorithms and spreadsheets that exist today allows people to apply them for a lower cost and with less complexity. However, spreadsheets linked to OR techniques, when directed to real problems, are still little explored in their full potential. In order to use them better, this article utilizes the Microsoft Office Excel to solve an optimization practical problem and decision-making of machining subcontracting. In general, although considered a frequent problem, is not of easy solution, optimize the mix of production versus outsourcing, because of the restrictions and resources available, it requests investments in specific software. In this way, this research aims to develop software to be called SOSU (Optimization Software for Machining Subcontracting). SOSU should introduce the best mix of internal and subcontracted machining for n types of parts that, over a certain period of time t, maximize capacity and meet all the demand at the lowest cost possible. The methodology adopted follows the bibliographic reference and it is assumed that the necessary data to prove from mathematical modeling of production areas and from a system of costs already structured. The nature of the problem justifies the application of Linear Programming (LP), Visual Basic for Applications (VBA) is used for computational implementation and interface with the user and the supplement Solver to find the solution. The analysis of the experiments show that the SOSU optimizes resources and improves the decision-making process, besides an easy operation, it can be implemented or quickly adapted and without the need of large investments.

Modelo matemático para determinação do custo e produção de energia na cultura da cana-de-açúcar

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

Análise econômica da eficiência da produção de cana-de-açúcar de fornecedores do Estado do Paraná

The sugarcane industry has been important in the Brazilian economy since the colonial period. The search for alternative energy sources has gained more prominence, by offering a product generating clean energy. With the opening of the Brazilian economy, the sector has undergone transformations operating in a free market environment requiring greater efficiency and competitiveness of those involved in order to stay in business. This scenario is producer/supplier independent, and social aspects related to their stay in the market. Although its share in sugarcane production is smaller than the plant itself, it is still considerable having reached around 20% to 25% in 2008 by employing labor, also production factors had an important economic impact in the regions where they operate. Therefore, this study aimed to estimate the economic efficiency and production of independent sugarcane producers in the state of Paraná through the DEA model. The Data envelopment analysis (DEA) is a nonparametric technique that, using linear programming constructs production borders from production units that employ similar technological processes to transform inputs into outputs.The results showed that of the total surveyed, 13.56% had maximum efficiency (an efficiency score equal to 1). The average efficiency under variable returns to scale (BCC-DEA) was 0.71024. One can thus conclude that for the majority of the samples collected, it might be better use of available resources to the in order to obtain the economic efficiency of the production process.

Funções penalidade para o tratamento das variáveis discretas do problema de fluxo de potência ótimo reativo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study

The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.

Binary integer programming formulations for scheduling in market-driven foundries

This paper describes the development and solution of binary integer formulations for production scheduling problems in market-driven foundries. This industrial sector is comprised of small and mid-sized companies with little or no automation, working with diversified production, involving several different metal alloy specifications in small tailor-made product lots. The characteristics and constraints involved in a typical production environment at these industries challenge the formulation of mathematical programming models that can be computationally solved when considering real applications. However, despite the interest on the part of these industries in counting on effective methods for production scheduling, there are few studies available on the subject. The computational tests prove the robustness and feasibility of proposed models in situations analogous to those found in production scheduling at the analyzed industrial sector. (C) 2010 Elsevier Ltd. All rights reserved.

Bounded solutions of fermions in the background of mixed vector-scalar inversely linear potentials

The problem of a fermion subject to a general mixing of vector and scalar potentials in a two-dimensional world is mapped into a Sturm-Liouville problem. Isolated bounded solutions are also searched. For the specific case of an inversely linear potential, which gives rise to an effective Kratzer potential in the Sturm-Liouville problem, exact bounded solutions are found in closed form. The case of a pure scalar potential with their isolated zero-energy solutions, already analyzed in a previous work, is obtained as a particular case. The behavior of the upper and lower components of the Dirac spinor is discussed in detail and some unusual results are revealed. The nonrelativistic limit of our results adds a new support to the conclusion that even-parity solutions to the nonrelativistic one-dimensional hydrogen atom do not exist. (c) 2004 Elsevier B.V. All rights reserved.

Klein-Gordon particles in mixed vector-scalar inversely linear potentials

The problem of a spinless particle subject to a general mixing of vector and scalar inversely linear potentials in a two-dimensional world is analyzed. Exact bounded solutions are found in closed form by imposing boundary conditions on the eigenfunctions which ensure that the effective Hamiltonian is Hermitian for all the points of the space. The nonrelativistic limit of our results adds a new support to the conclusion that even-parity solutions to the nonrelativistic one-dimensional hydrogen atom do not exist. (c) 2005 Elsevier B.V. All rights reserved.

Confinement of fermions by mixed vector-scalar linear potentials in two-dimensional space-time

The problem of confinement of fermions in 1 + 1 dimensions is approached with a linear potential in the Dirac equation by considering a mixing of Lorentz vector and scalar couplings. Analytical bound-states solutions are obtained when the scalar coupling is of sufficient intensity compared to the vector coupling. (C) 2002 Elsevier B.V. B.V. All rights reserved.

On Duffin-Kemmer-Petiau particles with a mixed minimal-nonminimal vector coupling and the nondegenerate bound-states for the one-dimensional inversely linear background

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation

Linear mixed effects models have been widely used in analysis of data where responses are clustered around some random effects, so it is not reasonable to assume independence between observations in the same cluster. In most biological applications, it is assumed that the distributions of the random effects and of the residuals are Gaussian. This makes inferences vulnerable to the presence of outliers. Here, linear mixed effects models with normal/independent residual distributions for robust inferences are described. Specific distributions examined include univariate and multivariate versions of the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted and Markov chain Monte Carlo is used to carry out the posterior analysis. The procedures are illustrated using birth weight data on rats in a texicological experiment. Results from the Gaussian and robust models are contrasted, and it is shown how the implementation can be used for outlier detection. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process in linear mixed models, and they are easily implemented using data augmentation and MCMC techniques.

Alocação otimizada de bancos de capacitores em sistemas de distribuição de energia elétrica através de metaheurísticas multiobjetivo

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