Constrained And Unconstrained Optimization
Mostrando 1-9 de 9 artigos, teses e dissertações.
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1. BUNDLE METHODS IN THE XXIst CENTURY: A BIRD'S-EYE VIEW
Bundle methods are often the algorithms of choice for nonsmooth convex optimization, especially if accuracy in the solution and reliability are a concern. We review several algorithms based on the bundle methodology that have been developed recently and that, unlike their forerunner variants, have the ability to provide exact solutions even if most of the ti
Pesqui. Oper.. Publicado em: 2014-12
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2. State estimation of chemical engineering systems tending to multiple solutions
A well-evaluated state covariance matrix avoids error propagation due to divergence issues and, thereby, it is crucial for a successful state estimator design. In this paper we investigate the performance of the state covariance matrices used in three unconstrained Extended Kalman Filter (EKF) formulations and one constrained EKF formulation (CEKF). As bench
Braz. J. Chem. Eng.. Publicado em: 2014-09
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3. Active-set strategy in Powell's method for optimization without derivatives
In this article we present an algorithm for solving bound constrained optimization problems without derivatives based on Powell's method [38] for derivative-free optimization. First we consider the unconstrained optimization problem. At each iteration a quadratic interpolation model of the objective function is constructed around the current iterate and this
Computational & Applied Mathematics. Publicado em: 2011
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4. Lagrange multipliers : geometrical and algebraic aspects and an application in chemical engineering in the methanol distillation / Multiplicadores de Lagrange : aspectos geometricos e algebricos e uma aplicação em engenharia quimica na destilação do metanol
This work begins with a brief historical overview of Fermat?s method to find maxima and minima without derivatives. In theoretical terms, the elements concerning maximum and minimum of functions of n variables are discussed, together with a detailed study of unconstrained optimization, focusing on the Fermat?s rule and the classification of critical points.
Publicado em: 2008
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5. Otimização de colunas de destilação : uma abordagem aplicada dos multiplicadores de Lagrange / Optimization of distillation comumns : an applied approach of the Lagrange multipliers
This work tackles the optimization of a distillation process of a binary mixture in a column with plates, which came from the methanol distillation in the production process of the biodiesel. More specifically, it considers the minimization of a cost objective function that encompass the heat rate supplied to the reboiler and the feed temperature, subject to
Publicado em: 2008
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6. Accelerating the Levenberg-Marquardt method for the minimization of the square of functions with box constraints / Acelerando o metodo de Levenberg-Marquardt para a minimização da soma de quadrados de funções com restrições de caixa
In this work, we present an active set algorithm for minimizing the sum of squares of smooth functions, with box constraints. The algorithm is highly inspired in the work of Birgin and Mart´inez [4]. The differences are concentrated on the chosen search direction and on the use of an acceleration technique to update the step. At each iteration, we define an
Publicado em: 2008
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7. Identificação de sistemas "on-line", otimização e controle avançado com o filtro de Kalman estendido / On line system identification, advanced control and optimization with the (Extended) Kalman filter
In the continuing competition between it will be more and more necessary to optimize current chemical processes in real time. To be able to optimize a plant in real time, there have to be various aspects to be fulfilled, such as measurement, reliability of the measurement and prediction of the process behaviour. In this work some of the aspects of such an ad
Publicado em: 2006
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8. Implementação de Equalizadores Allpass para Correção de Atraso de Grupo Empregando Técnicas de Otimização
Esta dissertação apresenta o desenvolvimento de um algoritmo, que utiliza métodos de otimização com o objetivo de obter filtros passa-tudo (allpass) estáveis para atuarem como equalizadores de atraso de grupo. O algoritmo obtém os coeficientes do filtro allpass a partir de uma resposta de atraso de grupo pré-definida. O projeto deste algoritmo envolv
Publicado em: 2005
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9. On the convergence properties of the projected gradient method for convex optimization
When applied to an unconstrained minimization problem with a convex objective, the steepest descent method has stronger convergence properties than in the noncovex case: the whole sequence converges to an optimal solution under the only hypothesis of existence of minimizers (i.e. without assuming e.g. boundedness of the level sets). In this paper we look at
Computational & Applied Mathematics. Publicado em: 2003