Search results for " OPTIMA"

showing 10 items of 220 documents

Optimal Impulse Control Problems and Linear Programming

2009

Optimal impulse control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions. In this paper, we identify a special class of optimal impulse control problems which are easy to solve. Easy to solve means that solution algorithms are polynomial in time and therefore suitable to the on-line implementation in real-time problems. We do this by using a paradigm borrowed from the Operations Research field. As main result, we present a solution algorithm that converges to the exact solution in polynomial time. Our approach consists in approximating the optimal impulse control problem via a binary linear programming proble…

PolynomialMathematical optimizationUnimodular matrixComputational complexity theoryLinear programmingbusiness.industryImpulse control hybrid systems optimal controlLocal search (optimization)Relaxation (approximation)Optimal controlbusinessTime complexityMathematics
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The linear saturated decentralized strategy for constrained flow control is asymptotically optimal

2013

We present an algorithm for constrained network flow control in the presence of an unknown demand. Our algorithm is decentralized in the sense that it is implemented by a team of agents, each controlling just the flow on a single arc of the network based only on the buffer levels at the nodes at the extremes of the arc, while ignoring the actions of other agents and the network topology. We prove that our algorithm is also stabilizing and steady-state optimal. Specifically, we show that it asymptotically produces the minimum-norm flow. We finally generalize our algorithm to networks with a linear dynamics and we prove that certain least-square optimality properties still hold.

Production-distribution systemsOptimizationMathematical optimizationRobust controlUncertain systemsMinimum normNetwork topologyMinimum norm flowControl theoryElectric network topologyConstrained flowUncertain systemsElectrical and Electronic EngineeringMathematicsFlow control (data)Network topologyAsymptotically optimalRobust control; OptimizationUncertain systemEthernet flow controlAsymptotically optimal Constrained flow Distributed flow control Minimum norm Network optimization Network topology Production-distribution systems Steady-state optimal; Algorithms Electric network topology Flow control Uncertain systems; OptimizationProduction-distribution systemFlow controlAsymptotically optimal algorithmControl and Systems EngineeringSteady-state optimalMinimum-cost flow problemDistributed flow controlRobust controlNetwork optimization; Distributed flow control; Production-distribution systems; Uncertain systems; Minimum norm flowNetwork optimizationAlgorithms
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Proximity and distance in spatial economic theory

1997

La proximité entre des éléments d’un ensemble évoque une certaine similitude entre un ou plusieurs de leurs attributs. Elle peut, en général, être évaluée par une distance. L’article revient d’abord sur l’idée de distance, son rôle et les modalités de son expression. Ensuite, il présente diverses représentations formalisées, il expose les contraintes qu’elles imposent dans la représentation de l’espace. Enfin, dans la mesure où la proximité d’un lieu est souvent définie par rapport à un ensemble d’autres sites, on met en évidence le rôle du choix d’une représentation de la distance dans la détermination du lieu qui offre la proximité optimale et l’influence du critère à partir duquel est dé…

Proximité optimaleEconomic theoryEconomicsStatisticsProximitéPsychologyReprésentations[ SHS.ECO ] Humanities and Social Sciences/Economies and financesOperations researchCognitive distance[SHS.ECO]Humanities and Social Sciences/Economics and Finance[SHS.ECO] Humanities and Social Sciences/Economics and FinanceDistance métrique
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Symmetry for positive critical points of Caffarelli–Kohn–Nirenberg inequalities

2022

Abstract We consider positive critical points of Caffarelli–Kohn–Nirenberg inequalities and prove a Liouville type result which allows us to give a complete classification of the solutions in a certain range of parameters, providing a symmetry result for positive solutions. The governing operator is a weighted p -Laplace operator, which we consider for a general p ∈ ( 1 , d ) . For p = 2 , the symmetry breaking region for extremals of Caffarelli–Kohn–Nirenberg inequalities was completely characterized in Dolbeault et al. (2016). Our results extend this result to a general p and are optimal in some cases.

Pure mathematicsApplied MathematicsOperator (physics)Caffarelli–Kohn–Nirenberg inequalities Classification of solutions Liouville-type theorem Optimal constant Quasilinear anisotropic elliptic equationsMathematics::Analysis of PDEsType (model theory)Range (mathematics)Settore MAT/05 - Analisi MatematicaSymmetry breakingSymmetry (geometry)Nirenberg and Matthaei experimentLaplace operatorAnalysisMathematics
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A Quasilinear Parabolic Equation with Quadratic Growth of the Gradient modeling Incomplete Financial Markets

2004

We consider a quasilinear parabolic equation with quadratic gradient terms. It arises in the modeling of an optimal portfolio which maximizes the expected utility from terminal wealth in incomplete markets consisting of risky assets and non-tradable state variables. The existence of solutions is shown by extending the monotonicity method of Frehse. Furthermore, we prove the uniqueness of weak solutions under a smallness condition on the derivatives of the covariance matrices with respect to the solution. The in influence of the non-tradable state variables on the optimal value function is illustrated by a numerical example.

Quadratic growthState variableQuadratic equationIncomplete marketsBellman equationMathematical analysisMonotonic functionUniquenessCovarianceQuasilinear PDE quadratic gradient existence and uniqueness of solutions optimal portfolio incomplete marketMathematicsSSRN Electronic Journal
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Ultrafast critical ground state preparation via bang-bang protocols

2020

The fast and faithful preparation of the ground state of quantum systems is a challenging task but crucial for several applications in the realm of quantum-based technologies. Decoherence poses a limit to the maximum time-window allowed to an experiment to faithfully achieve such desired states. This is of particular significance in critical systems, where the vanishing energy gap challenges an adiabatic ground state preparation. We show that a bang-bang protocol, consisting of a time evolution under two different values of an externally tunable parameter, allows for a high-fidelity ground state preparation in evolution times no longer than those required by the application of standard opti…

Quantum phase transitionQuantum decoherenceGeneral Physics and AstronomyFOS: Physical sciencesPhysics and Astronomy(all)Topology01 natural sciences010305 fluids & plasmasquantum optimal protocols/dk/atira/pure/subjectarea/asjc/31000103 physical sciencesQuantum information010306 general physicsAdiabatic processQuantumPhysicsquantum phase transitionsQuantum PhysicsTime evolutionOptimal controlquantum control quantum optimal protocols quantum phase transitionsQuantum Gases (cond-mat.quant-gas)Ground statequantum controlQuantum Physics (quant-ph)Condensed Matter - Quantum Gases
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3D digitization of transparent objects by polalization techniques in IR & by triangulation in UV

2011

Two non-conventional methods for the 3D digitization of transparent objects via non-contact measurement are reported in this thesis. 3D digitization is a well acknowledged technique for opaque objects and various commercial solutions based on different measurement approaches are available in the market offering different types of resolution at different prices. Since these techniques require a diffused or lambertian surface, their application to transparent surfaces fails. Indeed, rays reflected by the transparent surface are perturbed by diverse inter-reflections induced by the refractive properties of the object. Therefore, in industrial applications like quality control, the transparent …

Reconstruction par polarisation dans l'IRLow cost systemApproximation du modèle orthographique[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Objets transparentscoût)3D digitizationMéthode de validation des paramètres de StokesExcellent accuracyFluorescence tracking and characterizationTransparent objectsValidation method for optimal configuration setupScanning par laser UVIndustrialisable (en terme de précisionIndustrial applicationsOrthographic approximation approachShape from polarization in IRStokes parameters validation method[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Scanning from UV laserMéthode de validation pour une configuration optimale du système[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]Non telecentric lenseNumérisation 3DLentille non télécentrique"tracking" et caractérisation de la fluorescence
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Developement of new techniques of Optimal Control in Quantum Dynamics : from nuclear magnetic resonance to molecular physics

2011

The goal of this thesis is to apply the optimal control theory to the dynamics of quantum systems.The first part aim at introducing the tools of optimal control in quantum control which were initially developedin mathematics. This approch has been applied on different kinds of quantum system with small and largedimensions. The first part of this manuscript introduces the optimal control tools which are used with a pointof view suited to a public of physicists. In the second part these techniques are used to control the dynamics ofspins in NMR and MRI. The third part deals with the development of new iterative algorithms applied to thecontrol by laser fields of the rotational dynamics of lin…

Résonance magnétique nucléaire (RMN)[ PHYS.QPHY ] Physics [physics]/Quantum Physics [quant-ph]Nuclear Magnetic Resonance (NMR)Optimal Control[ MATH.MATH-GM ] Mathematics [math]/General Mathematics [math.GM]Magnetic Resonance Imaging (MRI)Contrôle localAlgorithme de KrotovAlgorithme monotoneBosonic Josephson Junction (BJJ)Pontryagin Maximum Principle (PMP)[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM][PHYS.QPHY]Physics [physics]/Quantum Physics [quant-ph][PHYS.COND.CM-GEN] Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other]Krotov AlgorithmLocal Control[PHYS.QPHY] Physics [physics]/Quantum Physics [quant-ph]Alignement moléculaireMonotonic AlgorihtmJonction Josephon bosonique[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM][ PHYS.COND.CM-GEN ] Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other]Imagerie par résonance magnétique (IRM)Quantum ControlMolecular Alignment[PHYS.COND.CM-GEN]Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other]Contrôle optimalPrincipe du maximum de Pontryagin (PMP)GRAPEContrôle quantique
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A Posteriori Methods

1998

A posteriori methods could also be called methods for generating Pareto optimal solutions. After the Pareto optimal set (or a part of it) has been generated, it is presented to the decision maker, who selects the most preferred among the alternatives. The inconveniences here are that the generation process is usually computationally expensive and sometimes in part, at least, difficult. On the other hand, it is hard for the decision maker to select from a large set of alternatives. One more important question is how to present or display the alternatives to the decision maker in an effective way. The working order in these methods is: 1) analyst, 2) decision maker.

Set (abstract data type)Generation processMultiobjective optimization problemPareto optimalMathematical optimizationWeighting coefficientOrder (exchange)Computer scienceA priori and a posterioriDecision maker
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A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling

2009

We consider the problem of allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. More specifically, the user is presented with `n ' sets of data points, S 1 , S 2 , ..., S n , where the set S i has N i points drawn from two classes {*** 1 , *** 2 }. A random sample in set S i belongs to *** 1 with probability u i and to *** 2 with probability 1 *** u i , with {u i }. i = 1, 2, ...n , being the quantities to be learnt. The problem is both interesting and non-trivial because while both n and each N i are large, the number of samples that can be drawn is bounded by a constant, c . We solve the problem by first modelling it a…

Set (abstract data type)Mathematical optimizationAsymptotically optimal algorithmHierarchy (mathematics)Learning automataComputer scienceBounded functionContinuous knapsack problemResource allocationStochastic optimization
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