78 resultados para Continuous constraint programming

em Biblioteca Digital da Produ


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Pipeline systems play a key role in the petroleum business. These operational systems provide connection between ports and/or oil fields and refineries (upstream), as well as between these and consumer markets (downstream). The purpose of this work is to propose a novel MINLP formulation based on a continuous time representation for the scheduling of multiproduct pipeline systems that must supply multiple consumer markets. Moreover, it also considers that the pipeline operates intermittently and that the pumping costs depend on the booster stations yield rates, which in turn may generate different flow rates. The proposed continuous time representation is compared with a previously developed discrete time representation [Rejowski, R., Jr., & Pinto, J. M. (2004). Efficient MILP formulations and valid cuts for multiproduct pipeline scheduling. Computers and Chemical Engineering, 28, 1511] in terms of solution quality and computational performance. The influence of the number of time intervals that represents the transfer operation is studied and several configurations for the booster stations are tested. Finally, the proposed formulation is applied to a larger case, in which several booster configurations with different numbers of stages are tested. (C) 2007 Elsevier Ltd. All rights reserved.

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Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

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A mixed integer continuous nonlinear model and a solution method for the problem of orthogonally packing identical rectangles within an arbitrary convex region are introduced in the present work. The convex region is assumed to be made of an isotropic material in such a way that arbitrary rotations of the items, preserving the orthogonality constraint, are allowed. The solution method is based on a combination of branch and bound and active-set strategies for bound-constrained minimization of smooth functions. Numerical results show the reliability of the presented approach. (C) 2010 Elsevier Ltd. All rights reserved.

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A Nonlinear Programming algorithm that converges to second-order stationary points is introduced in this paper. The main tool is a second-order negative-curvature method for box-constrained minimization of a certain class of functions that do not possess continuous second derivatives. This method is used to define an Augmented Lagrangian algorithm of PHR (Powell-Hestenes-Rockafellar) type. Convergence proofs under weak constraint qualifications are given. Numerical examples showing that the new method converges to second-order stationary points in situations in which first-order methods fail are exhibited.

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Two Augmented Lagrangian algorithms for solving KKT systems are introduced. The algorithms differ in the way in which penalty parameters are updated. Possibly infeasible accumulation points are characterized. It is proved that feasible limit points that satisfy the Constant Positive Linear Dependence constraint qualification are KKT solutions. Boundedness of the penalty parameters is proved under suitable assumptions. Numerical experiments are presented.

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In this work, we introduce a necessary sequential Approximate-Karush-Kuhn-Tucker (AKKT) condition for a point to be a solution of a continuous variational inequality, and we prove its relation with the Approximate Gradient Projection condition (AGP) of Garciga-Otero and Svaiter. We also prove that a slight variation of the AKKT condition is sufficient for a convex problem, either for variational inequalities or optimization. Sequential necessary conditions are more suitable to iterative methods than usual punctual conditions relying on constraint qualifications. The AKKT property holds at a solution independently of the fulfillment of a constraint qualification, but when a weak one holds, we can guarantee the validity of the KKT conditions.

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This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs) taking values in a general Borel space and with compact action space depending on the state variable. The control variable acts on the jump rate and transition measure of the PDMP, and the running and boundary costs are assumed to be positive but not necessarily bounded. Our first main result is to obtain an optimality equation for the long run average cost in terms of a discrete-time optimality equation related to the embedded Markov chain given by the postjump location of the PDMP. Our second main result guarantees the existence of a feedback measurable selector for the discrete-time optimality equation by establishing a connection between this equation and an integro-differential equation. Our final main result is to obtain some sufficient conditions for the existence of a solution for a discrete-time optimality inequality and an ordinary optimal feedback control for the long run average cost using the so-called vanishing discount approach. Two examples are presented illustrating the possible applications of the results developed in the paper.

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Based on high-resolution spectra obtained with the MIKE spectrograph on the Magellan telescopes, we present detailed elemental abundances for 20 red giant stars in the outer Galactic disk, located at Galactocentric distances between 9 and 13 kpc. The outer disk sample is complemented with samples of red giants from the inner Galactic disk and the solar neighborhood, analyzed using identical methods. For Galactocentric distances beyond 10 kpc, we only find chemical patterns associated with the local thin disk, even for stars far above the Galactic plane. Our results show that the relative densities of the thick and thin disks are dramatically different from the solar neighborhood, and we therefore suggest that the radial scale length of the thick disk is much shorter than that of the thin disk. We make a first estimate of the thick disk scale length of L(thick) = 2.0 kpc, assuming L(thin) = 3.8 kpc for the thin disk. We suggest that radial migration may explain the lack of radial age, metallicity, and abundance gradients in the thick disk, possibly also explaining the link between the thick disk and the metal-poor bulge.

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We show that scalable multipartite entanglement among light fields may be generated by optical parametric oscillators (OPOs). The tripartite entanglement existent among the three bright beams produced by a single OPO-pump, signal, and idler-is scalable to a system of many OPOs by pumping them in cascade with the same optical field. This latter serves as an entanglement distributor. The special case of two OPOs is studied, as it is shown that the resulting five bright beams share genuine multipartite entanglement. In addition, the structure of entanglement distribution among the fields can be manipulated to some degree by tuning the incident pump power. The scalability to many fields is straightforward, allowing an alternative implementation of a multipartite quantum information network with continuous variables.

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We study the structural phase transitions in confined systems of strongly interacting particles. We consider infinite quasi-one-dimensional systems with different pairwise repulsive interactions in the presence of an external confinement following a power law. Within the framework of Landau's theory, we find the necessary conditions to observe continuous transitions and demonstrate that the only allowed continuous transition is between the single-and the double-chain configurations and that it only takes place when the confinement is parabolic. We determine analytically the behavior of the system at the transition point and calculate the critical exponents. Furthermore, we perform Monte Carlo simulations and find a perfect agreement between theory and numerics.

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The uptake of ascorbate by neuroblastoma cells using a ruthenium oxide hexacyanoferrate (RuOHCF)-modified carbon fiber disc (CFD) microelectrode (r = 14.5 mu m) was investigated. By use of the proposed electrochemical sensor the amperometric determination of ascorbate was performed at 0.0 V in minimum essential medium (MEM, pH = 7.2) with a limit of detection of 25 mu mol L(-1). Under the optimum experimental conditions, no interference from MEM constituents and reduced glutathione (used to prevent the oxidation of ascorbate during the experiments) was noticed. The stability of the RuOHCF-modified electrode response was studied by measuring the sensitivity over an extended period of time (120 h), a decrease of around 10% being noticed at the end of the experiment. The rate of ascorbate uptake by control human neuroblastoma SH-SY5Y cells, and cells transfected with wild-type Cu,Zn-superoxide dismutase (SOD WT) or with a mutant typical of familial amyotrophic lateral sclerosis (SOD G93A), was in agreement with the level of oxidative stress in these cells. The usefulness of the RuOHCF-modified microelectrode for in vivo monitoring of ascorbate inside neuroblastoma cells was also demonstrated.

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Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

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A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.

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It has been suggested that the temporal control of rhythmic unimianual movements is different between tasks requiring continuous (e.g., circle drawing) and discontinuous movements (e.g., finger tapping). Specifically, for continuous movements temporal regularities are ail emergent property, whereas for tasks that involve discontinuities timing is ail explicit part of the action goal. The present experiment further investigated the control of continuous and discontinuous movements by comparing the coordination dynamics and attentional demands of bimanual continuous circle drawing with bimanual intermittent circle drawing. The intermittent task required participants to insert a 400 ms pause between each cycle while circling. Using dual-task methodology, 15 right-handed participants performed the two circle drawing tasks, while vocally responding to randomly presented auditory probes. The circle drawing tasks were performed in symmetrical and asymmetrical coordination modes and at movement frequencies of 1 Hz and 1.7 Hz. Intermittent circle drawing exhibited superior spatial and temporal accuracy and stability than continuous circle drawing supporting the hypothesis that the two tasks have different underlying control processes. In terms of attentional cost, probe RT was significantly slower during the intermittent circle drawing task than the continuous circle drawing task across both coordination modes and movement frequencies. Of interest was the finding that in the intermittent circling task reaction time (RT) to probes presented during the pause between cycles did not differ from the RT to probes occurring during the circling movement. The differences in attentional demands between the intermittent and continuous circle drawing tasks may reflect the operation of explicit event timing and implicit emergent timing processes, respectively. (C) 2008 Elsevier B.V. All rights reserved.