Search results for "Mathematical optimization"

showing 10 items of 1300 documents

Regularity and strong sufficient optimality conditions in differentiable optimization problems

1993

This paper studies the metric regularity of multivalued functions on Banach spaces, tangential approximations of the feasible set and strong sufficient optimality conditions of a parametrized optimization problem minimize The results are applied to the tangent approximations and the local stability properties of solutions of this perturbed optimization problem.

Mathematical optimizationControl and OptimizationOptimization problemMultivalued functionFeasible regionStability (learning theory)Banach spaceTangentComputer Science ApplicationsSignal ProcessingMetric (mathematics)Differentiable functionAnalysisMathematicsNumerical Functional Analysis and Optimization
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Shape optimization of elasto-plastic bodies under plane strains: Sensitivity analysis and numerical implementation

1992

Optimal shape design problems for an elastic body made from physically nonlinear material are presented. Sensitivity analysis is done by differentiating the discrete equations of equilibrium. Numerical examples are included.

Mathematical optimizationControl and OptimizationPlane (geometry)Structural mechanicsMathematical analysisGeneral EngineeringOptimal controlComputer Graphics and Computer-Aided DesignFinite element methodComputer Science ApplicationsNonlinear systemControl and Systems EngineeringShape optimizationSensitivity (control systems)SoftwareMathematicsPlane stressStructural Optimization
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Sensitivity analysis for optimal shape design problems

1989

Various methods for performing the sensitivity analysis in solving optimal shape design problems are outlined. The methods are illustrated in detail in the finite setting of a unilateral boundary value problem of the Dirichlet-Signorini type. The methods are compared in several numerical examples.

Mathematical optimizationControl and OptimizationShape designControl and Systems EngineeringGeneral EngineeringBoundary value problemSensitivity (control systems)Type (model theory)Engineering design processComputer Graphics and Computer-Aided DesignSoftwareComputer Science ApplicationsMathematicsStructural Optimization
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Team Theory and Person-by-Person Optimization with Binary Decisions

2012

In this paper, we extend the notion of person-by-person (pbp) optimization to binary decision spaces. The novelty of our approach is the adaptation to a dynamic team context of notions borrowed from the pseudo-boolean optimization field as completely local-global or unimodal functions and submodularity. We also generalize the concept of pbp optimization to the case where groups of $m$ decisions makers make joint decisions sequentially, which we refer to as $m$b$m$ optimization. The main contribution is a description of sufficient conditions, verifiable in polynomial time, under which a pbp or an $m$b$m$ optimization algorithm converges to the team-optimum. As a second contribution, we prese…

Mathematical optimizationControl and Optimizationcontrol optimizationBinary decision diagramApplied MathematicsTeam Theory; Person-by-Person Optimization; Pseudo-Boolean OptimizationApproximation algorithmState vectorTeam TheoryPerson-by-Person OptimizationSubmodular set functionVector optimizationPseudo-Boolean OptimizationComplete informationSettore MAT/09 - Ricerca OperativaGreedy algorithmTime complexityMathematicsSIAM Journal on Control and Optimization
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Distributed <inline-formula> <tex-math notation="TeX">$n$</tex-math></inline-formula>-Player Approachability and Consensus in…

2015

We study a distributed allocation process where, at each time, every player: i) proposes a new bid based on the average utilities produced up to that time, ii) adjusts such allocations based on the inputs received from its neighbors, and iii) generates and allocates new utilities. The average allocations evolve according to a doubly (over time and space) averaging algorithm. We study conditions under which the average allocations reach consensus to any point within a predefined target set even in the presence of adversarial disturbances. Motivations arise in the context of coalitional games with transferable utilities (TU) where the target set is any set of allocations that makes the grand …

Mathematical optimizationControl and Systems EngineeringComputer scienceRobustness (computer science)Electrical and Electronic EngineeringApproachabilityGrand coalitionGame theoryComputer Science ApplicationsIEEE Transactions on Automatic Control
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The solution of a ‘ fixed-target’—model by an approach of system analysis

1974

Abstract A general approach fur economic systems is combined with a concrete ‘ fixed-target’—model. The consideration of convergence leads—under conditions of a stable solution and two targets—to the result that five numerical restrictions must be recognized when treating the two instruments. Generalizations of the discussed illustrative model are possible.

Mathematical optimizationControl and Systems EngineeringConvergence (routing)Computer Science ApplicationsTheoretical Computer ScienceMathematicsInternational Journal of Systems Science
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How to simulate normal data sets with the desired correlation structure

2010

The Cholesky decomposition is a widely used method to draw samples from multivariate normal distribution with non-singular covariance matrices. In this work we introduce a simple method by using singular value decomposition (SVD) to simulate multivariate normal data even if the covariance matrix is singular, which is often the case in chemometric problems. The covariance matrix can be specified by the user or can be generated by specifying a subset of the eigenvalues. The latter can be an advantage for simulating data sets with a particular latent structure. This can be useful for testing the performance of chemometric methods with data sets matching the theoretical conditions for their app…

Mathematical optimizationCovariance functionCovariance matrixProcess Chemistry and TechnologyMathematicsofComputing_NUMERICALANALYSISMultivariate normal distributionCovarianceComputer Science ApplicationsAnalytical ChemistryEstimation of covariance matricesScatter matrixMatrix normal distributionCMA-ESAlgorithmComputer Science::DatabasesSpectroscopySoftwareMathematicsChemometrics and Intelligent Laboratory Systems
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Statistical validation of rival models for observable stochastic process and its identification

2011

In this paper, for statistical validation of rival (analytical or simulation) models collected for modeling observable process in stochastic system (say, transportation or service system), a uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens-Fisher problem when covariance matrices of multivariate normal populations (compared with respect to their means) are different and unknown. The test makes use of an invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters. The sample size and thresho…

Mathematical optimizationCovariance matrixStochastic processMultivariate normal distributionCovarianceInvariant (mathematics)Null hypothesisBehrens–Fisher problemStatisticMathematics2011 Baltic Congress on Future Internet and Communications
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Cross-Efficiency in Fuzzy Data Envelopment Analysis (FDEA): Some Proposals

2013

Different techniques have been proposed in the literature to rank decision making units (DMUs) in the context of Fuzzy Data Envelopment Analysis. In our opinion, those that result from using a ranking method to order the fuzzy efficiencies obtained are susceptible to a serious criticism: they are not based on objective criteria. Cross-efficiency evaluation was introduced as an extension of DEA aimed at ranking the DMUs. This methodology has found a significant number of applications and has been extensively investigated. In this chapter, we discuss some difficulties that arise with the definition of fuzzy cross-efficiencies and we propose a fuzzy cross-efficiency evaluation based on the FDE…

Mathematical optimizationCross efficiencyEfficiencyComputer scienceFuzzy mathematical programmingData envelopment analysisMultiplier (economics)Fuzzy data envelopment analysisFuzzy logic
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A multi-sphere particle numerical model for non-invasive investigations of neuronal human brain activity

2013

In this paper, a multi-sphere particle method is built- up in order to estimate the solution of the Poisson's equation with Neumann boundary conditions describing the neuronal human brain activity. The partial difierential equations governing the relationships between neural current sources and the data produced by neuroimaging technique, are able to compute the scalp potential and magnetic fleld distributions generated by the neural activity. A numerical approach is proposed with current dipoles as current sources and going on in the computation by avoiding the mesh construction. The current dipoles are into an homogeneous spherical domain modeling the head and the computational approach i…

Mathematical optimizationCurrent (mathematics)Quantitative Biology::Neurons and CognitionComputer scienceComputationNon invasiveMathematical analysisDomain modelPoisson distributionElectronic Optical and Magnetic MaterialsDipolesymbols.namesakeBio-magnetic fields Human brain activity meshless numerical methodSettore ING-IND/31 - ElettrotecnicaNeumann boundary conditionsymbolsParticle
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