42 resultados para NONCONVEX NLPS


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A novel global optimization method based on an Augmented Lagrangian framework is introduced for continuous constrained nonlinear optimization problems. At each outer iteration k the method requires the epsilon(k)-global minimization of the Augmented Lagrangian with simple constraints, where epsilon(k) -> epsilon. Global convergence to an epsilon-global minimizer of the original problem is proved. The subproblems are solved using the alpha BB method. Numerical experiments are presented.

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We describe finite sets of points, called sentinels, which allow us to decide if isometric copies of polygons, convex or not, intersect. As an example of the applicability of the concept of sentinel, we explain how they can be used to formulate an algorithm based on the optimization of differentiable models to pack polygons in convex sets. Mathematical subject classification: 90C53, 65K05.

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In this paper we propose and analyse a hybrid numerical-asymptotic boundary element method for the solution of problems of high frequency acoustic scattering by a class of sound-soft nonconvex polygons. The approximation space is enriched with carefully chosen oscillatory basis functions; these are selected via a study of the high frequency asymptotic behaviour of the solution. We demonstrate via a rigorous error analysis, supported by numerical examples, that to achieve any desired accuracy it is sufficient for the number of degrees of freedom to grow only in proportion to the logarithm of the frequency as the frequency increases, in contrast to the at least linear growth required by conventional methods. This appears to be the first such numerical analysis result for any problem of scattering by a nonconvex obstacle. Our analysis is based on new frequency-explicit bounds on the normal derivative of the solution on the boundary and on its analytic continuation into the complex plane.

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In this paper, we consider a vector optimization problem where all functions involved are defined on Banach spaces. We obtain necessary and sufficient criteria for optimality in the form of Karush-Kuhn-Tucker conditions. We also introduce a nonsmooth dual problem and provide duality theorems.

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Introducing an appropriate inclusion between approximate minima associated with two nonconvex functions, we derive explicit relations between the closed convex hulls of these functions. The formula we obtain goes beyond the so-called epi-pointed property of functions which is usually concerned with such a topic.

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In recent times the Douglas–Rachford algorithm has been observed empirically to solve a variety of nonconvex feasibility problems including those of a combinatorial nature. For many of these problems current theory is not sufficient to explain this observed success and is mainly concerned with questions of local convergence. In this paper we analyze global behavior of the method for finding a point in the intersection of a half-space and a potentially non-convex set which is assumed to satisfy a well-quasi-ordering property or a property weaker than compactness. In particular, the special case in which the second set is finite is covered by our framework and provides a prototypical setting for combinatorial optimization problems.

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We consider the question whether the assumption of convexity of the set involved in Clarke-Ledyaev inequality can be relaxed. In the case when the point is outside the convex hull of the set we show that Clarke-Ledyaev type inequality holds if and only if there is certain geometrical relation between the point and the set.

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A scenario-based two-stage stochastic programming model for gas production network planning under uncertainty is usually a large-scale nonconvex mixed-integer nonlinear programme (MINLP), which can be efficiently solved to global optimality with nonconvex generalized Benders decomposition (NGBD). This paper is concerned with the parallelization of NGBD to exploit multiple available computing resources. Three parallelization strategies are proposed, namely, naive scenario parallelization, adaptive scenario parallelization, and adaptive scenario and bounding parallelization. Case study of two industrial natural gas production network planning problems shows that, while the NGBD without parallelization is already faster than a state-of-the-art global optimization solver by an order of magnitude, the parallelization can improve the efficiency by several times on computers with multicore processors. The adaptive scenario and bounding parallelization achieves the best overall performance among the three proposed parallelization strategies.

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Immune challenges during neonatal period may permanently program immune responses later in life, including endotoxin fever. We tested the hypothesis that neonatal endotoxin exposure affects stress fever in adult rats. In control rats (treated with saline as neonates; nSal) body temperature peaked similar to 1.5 degrees C during open-field stress, whereas in rats exposed to endotoxin (lipopolysaccharide, LPS) as neonates (nLPS) stress fever was significantly attenuated. Following stress, plasma corticosterone levels significantly increased from 74.29 +/- 7.05 ng ml(-1) to 226.29 +/- 9.87 ng ml(-1) in nSal rats, and from 83.43 +/- 10.31 ng ml(-1) to 324.7 +/- 36.87 ng ml(-1) in nLPS rats. Animals treated with LPS as neonates and adrenalectomized one week before experimentation no longer displayed the attenuated febrile response to stress. This attenuated stress fever caused by an increased corticosterone secretion is likely to be linked to an inhibitory effect of glucocorticoids on cyclooxygenase activity/PGE(2) production in preoptic/anteroventral third ventricular region (AV3V) since stress failed to cause a significant increase in PGE(2) in nLPS rats, and this effect was reverted by adrenalectomy. Altogether, the present results indicate that endogenous glucocorticoids are key modulators of the attenuated stress fever in adult rats treated with LPS as neonates, and they act downregulating PGE(2) production in AV3V. Moreover, our findings also support the notion that neonatal immune stimulus affects programming of stress responses during adulthood, despite the fact that inflammation and stress are two distinct processes mediated largely by different neurobiological mechanisms. (C) 2010 Elsevier B.V. All rights reserved.

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We consider a fluid of hard boomerangs, each composed of two hard spherocylinders joined at their ends at an angle Psi. The resulting particle is nonconvex and biaxial. The occurence of nematic order in such a system has been investigated using Straley's theory, which is a simplificaton of Onsager's second-virial treatment of long hard rods, and by bifurcation analysis. The excluded volume of two hard boomerangs has been approximated by the sum of excluded volumes of pairs of constituent spherocylinders, and the angle-dependent second-virial coefficient has been replaced by a low-order interpolating function. At the so-called Landau point, Psi(Landau)approximate to 107.4 degrees, the fluid undergoes a continuous transition from the isotropic to a biaxial nematic (B) phase. For Psi not equal Psi(Landau) ordering is via a first-order transition into a rod-like uniaxial nematic phase (N(+)) if Psi > Psi(Landau), or a plate-like uniaxial nematic (N(-)) phase if Psi < Psi(Landau). The B phase is separated from the N(+) and N(-) phases by two lines of continuous transitions meeting at the Landau point. This topology of the phase diagram is in agreement with previous studies of spheroplatelets and biaxial ellipsoids. We have checked the accuracy of our theory by performing numerical calculations of the angle-dependent second virial coefficient, which yields Psi(Landau)approximate to 110 degrees for very long rods, and Psi(Landau)approximate to 90 degrees for short rods. In the latter case, the I-N transitions occur at unphysically high packing fractions, reflecting the inappropriateness of the second-virial approximation in this limit.

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Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em Informática

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Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

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INTRODUCTION: Late presentation to HIV care leads to increased morbidity and mortality. We explored risk factors and reasons for late HIV testing and presentation to care in the nationally representative Swiss HIV Cohort Study (SHCS). METHODS: Adult patients enrolled in the SHCS between July 2009 and June 2012 were included. An initial CD4 count <350 cells/µl or an AIDS-defining illness defined late presentation. Demographic and behavioural characteristics of late presenters (LPs) were compared with those of non-late presenters (NLPs). Information on self-reported, individual barriers to HIV testing and care were obtained during face-to-face interviews. RESULTS: Of 1366 patients included, 680 (49.8%) were LPs. Seventy-two percent of eligible patients took part in the survey. LPs were more likely to be female (p<0.001) or from sub-Saharan Africa (p<0.001) and less likely to be highly educated (p=0.002) or men who have sex with men (p<0.001). LPs were more likely to have their first HIV test following a doctor's suggestion (p=0.01), and NLPs in the context of a regular check-up (p=0.02) or after a specific risk situation (p<0.001). The main reasons for late HIV testing were "did not feel at risk" (72%), "did not feel ill" (65%) and "did not know the symptoms of HIV" (51%). Seventy-one percent of the participants were symptomatic during the year preceding HIV diagnosis and the majority consulted a physician for these symptoms. CONCLUSIONS: In Switzerland, late presentation to care is driven by late HIV testing due to low risk perception and lack of awareness about HIV. Tailored HIV testing strategies and enhanced provider-initiated testing are urgently needed.

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Esta disertación busca estudiar los mecanismos de transmisión que vinculan el comportamiento de agentes y firmas con las asimetrías presentes en los ciclos económicos. Para lograr esto, se construyeron tres modelos DSGE. El en primer capítulo, el supuesto de función cuadrática simétrica de ajuste de la inversión fue removido, y el modelo canónico RBC fue reformulado suponiendo que des-invertir es más costoso que invertir una unidad de capital físico. En el segundo capítulo, la contribución más importante de esta disertación es presentada: la construcción de una función de utilidad general que anida aversión a la pérdida, aversión al riesgo y formación de hábitos, por medio de una función de transición suave. La razón para hacerlo así es el hecho de que los individuos son aversos a la pérdidad en recesiones, y son aversos al riesgo en auges. En el tercer capítulo, las asimetrías en los ciclos económicos son analizadas junto con ajuste asimétrico en precios y salarios en un contexto neokeynesiano, con el fin de encontrar una explicación teórica de la bien documentada asimetría presente en la Curva de Phillips.

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In recent years nonpolynomial finite element methods have received increasing attention for the efficient solution of wave problems. As with their close cousin the method of particular solutions, high efficiency comes from using solutions to the Helmholtz equation as basis functions. We present and analyze such a method for the scattering of two-dimensional scalar waves from a polygonal domain that achieves exponential convergence purely by increasing the number of basis functions in each element. Key ingredients are the use of basis functions that capture the singularities at corners and the representation of the scattered field towards infinity by a combination of fundamental solutions. The solution is obtained by minimizing a least-squares functional, which we discretize in such a way that a matrix least-squares problem is obtained. We give computable exponential bounds on the rate of convergence of the least-squares functional that are in very good agreement with the observed numerical convergence. Challenging numerical examples, including a nonconvex polygon with several corner singularities, and a cavity domain, are solved to around 10 digits of accuracy with a few seconds of CPU time. The examples are implemented concisely with MPSpack, a MATLAB toolbox for wave computations with nonpolynomial basis functions, developed by the authors. A code example is included.