Search results for " optimization."

showing 10 items of 2333 documents

Generalized conditions for genuine multipartite continuous-variable entanglement

2015

We derive a hierarchy of continuous-variable multipartite entanglement conditions in terms of second-order moments of position and momentum operators that generalizes existing criteria. Each condition corresponds to a convex optimization problem which, given the covariance matrix of the state, can be numerically solved in a straightforward way. The conditions are independent of partial transposition and thus are also able to detect bound entangled states. Our approach can be used to obtain an analytical condition for genuine multipartite entanglement. We demonstrate that even a special case of our conditions can detect entanglement very efficiently. Using multi-objective optimization it is …

PhysicsQuantum PhysicsCovariance matrixFOS: Physical sciencesQuantum entanglementQuantum PhysicsSquashed entanglementMultipartite entanglementAtomic and Molecular Physics and OpticsMultipartitePosition (vector)Convex optimizationApplied mathematicsW stateQuantum Physics (quant-ph)
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Domain-wall excitations in the two-dimensional Ising spin glass

2018

The Ising spin glass in two dimensions exhibits rich behavior with subtle differences in the scaling for different coupling distributions. We use recently developed mappings to graph-theoretic problems together with highly efficient implementations of combinatorial optimization algorithms to determine exact ground states for systems on square lattices with up to $10\,000\times 10\,000$ spins. While these mappings only work for planar graphs, for example for systems with periodic boundary conditions in at most one direction, we suggest here an iterative windowing technique that allows one to determine ground states for fully periodic samples up to sizes similar to those for the open-periodic…

PhysicsQuantum PhysicsSpin glassStatistical Mechanics (cond-mat.stat-mech)SpinsPhase (waves)FOS: Physical sciencesDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComputational Physics (physics.comp-ph)01 natural sciences010305 fluids & plasmasTheoretical physicsDomain wall (magnetism)Spin wave0103 physical sciencesCombinatorial optimizationIsing spinQuantum Physics (quant-ph)010306 general physicsPhysics - Computational PhysicsCritical exponentCondensed Matter - Statistical MechanicsPhysical Review B
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Shape Optimization in Contact Problems. 1. Design of an Elastic Body. 2. Design of an Elastic Perfectly Plastic Body

1986

The optimal shape design of a two dimensional body on a rigid foundation is analyzed. The problem is how to find the boundary part of the body where the unilateral boundary conditions are assumed in such a way that a certain energy integral (total potential energy, for example) will be minimized. It is assumed that the material of the body is elastic. Some remarks will be given concerning the design of an elastic perfectly plastic body. Numerical examples will be given.

PhysicsShape designMathematical analysisFoundation (engineering)Boundary (topology)Shape optimizationShape optimization problemBoundary value problemPotential energyEnergy (signal processing)
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Shape design optimization in 2D aerodynamics using Genetic Algorithms on parallel computers

1996

Publisher Summary This chapter presents two Shape Optimization problems for two dimensional airfoil designs. The first one is a reconstruction problem for an airfoil when the velocity of the flow is known on the surface of airfoil. The second problem is to minimize the shock drag of an airfoil at transonic regime. The flow is modeled by the full potential equations. The discretization of the state equation is done using the finite element method and the resulting non-linear system of equations is solved by using a multi-grid method. The non-linear minimization process corresponding to the shape optimization problems are solved by a parallel implementation of a genetic algorithm (GA). Some n…

Physics::Fluid DynamicsAirfoilOptimal designMathematical optimizationDiscretizationApplied mathematicsShape optimizationAerodynamicsTransonicFinite element methodMathematicsSequential quadratic programming
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Models and solution methods for the uncapacitatedr-allocationp-hub equitable center problem

2017

Hub networks are commonly used in telecommunications and logistics to connect origins to destinations in situations where a direct connection between each origin–destination (o-d) pair is impractical or too costly. Hubs serve as switching points to consolidate and route traffic in order to realize economies of scale. The main decisions associated with hub-network problems include (1) determining the number of hubs (p), (2) selecting the p-nodes in the network that will serve as hubs, (3) allocating non-hub nodes (terminals) to up to r-hubs, and (4) routing the pairwise o-d traffic. Typically, hub location problems include all four decisions while hub allocation problems assume that the valu…

Physics::Physics and SocietyMathematical optimization021103 operations researchTotal costComputer scienceQuantitative Biology::Molecular NetworksStrategy and ManagementQuality of serviceMaximum cost0211 other engineering and technologiesComputer Science::Social and Information Networks02 engineering and technologyManagement Science and Operations ResearchFacility location problemComputer Science ApplicationsEconomies of scaleComputingMethodologies_PATTERNRECOGNITIONManagement of Technology and Innovation0202 electrical engineering electronic engineering information engineeringComputingMilieux_COMPUTERSANDSOCIETY020201 artificial intelligence & image processingPairwise comparisonCenter (algebra and category theory)Business and International ManagementRouting (electronic design automation)International Transactions in Operational Research
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Stochastic description of traffic breakdown

2003

We present a comparison of nucleation in an isothermal-isochoric container with traffic congestion on a one-lane freeway. The analysis is based, in both cases, on the probabilistic description by stochastic master equations. Further we analyze the characteristic features of traffic breakdowns. To describe this phenomenon we apply the stochastic model regarding the jam emergence to the formation of a large car cluster on the highway.

Physics::Physics and SocietyMathematical optimizationEngineeringTraffic congestion reconstruction with Kerner's three-phase theoryStochastic modellingbusiness.industryTraffic flowTraffic congestionMaster equationContainer (abstract data type)Three-phase traffic theorybusinessTraffic generation modelSimulationSPIE Proceedings
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Current Evidence, Challenges, and Opportunities of Physiologically Based Pharmacokinetic Models of Atorvastatin for Decision Making

2021

Atorvastatin (ATS) is the gold-standard treatment worldwide for the management of hypercholesterolemia and prevention of cardiovascular diseases associated with dyslipidemia. Physiologically based pharmacokinetic (PBPK) models have been positioned as a valuable tool for the characterization of complex pharmacokinetic (PK) processes and its extrapolation in special sub-groups of the population, leading to regulatory recognition. Several PBPK models of ATS have been published in the recent years, addressing different aspects of the PK properties of ATS. Therefore, the aims of this review are (i) to summarize the physicochemical and pharmacokinetic characteristics involved in the time-course o…

Physiologically based pharmacokinetic modellingModel predictionAtorvastatinPopulationPharmaceutical ScienceReviewTarget populationComputational biologyP-glycoprotein030226 pharmacology & pharmacy03 medical and health sciencesPharmacy and materia medica0302 clinical medicinePharmacokineticsmedicineopen acid formeducationeducation.field_of_studybusiness.industrysolubilityatorvastatinactive metabolitesRS1-441lactonizationDose optimizationMetabolic enzymes030220 oncology & carcinogenesisbusinessmedicine.drugPharmaceutics
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Efficient full decay inversion of MRS data with a stretched-exponential approximation of the distribution

2012

SUMMARY We present a new, efficient and accurate forward modelling and inversion scheme for magnetic resonance sounding (MRS) data. MRS, also called surface-nuclear magnetic resonance (surface-NMR), is the only non-invasive geophysical technique that directly detects free water in the subsurface. Based on the physical principle of NMR, protons of the water molecules in the subsurface are excited at a specific frequency, and the superposition of signals from all protons within the excited earth volume is measured to estimate the subsurface water content and other hydrological parameters. In this paper, a new inversion scheme is presented in which the entire data set is used, and multi-expone…

Piecewise linear functionMathematical optimizationSuperposition principleGeophysicsAmplitudeDiscretizationGeochemistry and PetrologyComputationMathematical analysisSynthetic dataMathematicsMagnetic fieldExponential functionGeophysical Journal International
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APROS-NIMBUS: Dynamic Process Simulator and Interactive Multiobjective Optimization in Plant Automation

2013

Abstract Virtual commissioning of chemical plants often involves a dynamic simulator and an optimization method. This paper demonstrates the integration of APROS, a dynamic process simulator and IND-NIMBUS, an interactive multiobjective optimization software. We implement a multiobjective concentration control problem in APROS involving conflicting objectives and employ a decision maker to interact with IND-NIMBUS and express his preference information to finally obtain his most preferred solution. The results of this study show that APROS and IND-NIMBUS can be integrated and an interactive multiobjective optimization method can help the decision maker in exploring trade-offs among conflict…

Plant automationpareto optimalityComputer scienceProcess (engineering)business.industryControl (management)multiple criteria decision makingDecision makerMulti-objective optimizationdecision makingSoftwareConflicting objectivesbusinessSimulation
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Variational multiframe restoration of images degraded by noisy (stochastic) blur kernels

2013

This article introduces and explores a class of degradation models in which an image is blurred by a noisy (stochastic) point spread function (PSF). The aim is to restore a sharper and cleaner image from the degraded one. Due to the highly ill-posed nature of the problem, we propose to recover the image given a sequence of several observed degraded images or multiframes. Thus we adopt the idea of the multiframe approach introduced for image super-resolution, which reduces distortions appearing in the degraded images. Moreover, we formulate variational minimization problems with the robust (local or nonlocal) L^1 edge-preserving regularizing energy functionals, unlike prior works dealing wit…

Point spread functionSequenceMathematical optimizationApplied MathematicsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION010103 numerical & computational mathematics02 engineering and technology01 natural sciencesImage (mathematics)Computational MathematicsComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSegmentationMinification0101 mathematicsAlgorithmEnergy (signal processing)Image restorationDegradation (telecommunications)MathematicsJournal of Computational and Applied Mathematics
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