Search results for "Mathematics::Optimization and Control"

showing 10 items of 30 documents

Some properties of [tr(Q2p)]12p with application to linear minimax estimation

1990

Abstract A nondifferentiable minimization problem is considered which occurs in linear minimax estimation. This problem is solved by replacing the nondifferentiable maximal eigenvalue of a real nonnegative definite matrix Q with [tr( Q 2 p )] 1/2 p . It is shown that any descent algorithm with inexact step-length rule can be used to obtain linear minimax estimators for the parameter vector of a parameter-restricted linear model.

Discrete mathematicsNumerical AnalysisAlgebra and Number TheoryMinimization problemLinear modelMathematics::Optimization and ControlMinimaxMinimax approximation algorithmMatrix (mathematics)Discrete Mathematics and CombinatoricsGeometry and TopologyMinimax estimatorDescent algorithmEigenvalues and eigenvectorsMathematicsLinear Algebra and its Applications
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On the proper homotopy invariance of the Tucker property

2006

A non-compact polyhedron P is Tucker if, for any compact subset K ⊂ P, the fundamental group π1(P − K) is finitely generated. The main result of this note is that a manifold which is proper homotopy equivalent to a Tucker polyhedron is Tucker. We use Poenaru’s theory of the equivalence relations forced by the singularities of a non-degenerate simplicial map.

Fundamental groupHomotopy lifting propertyApplied MathematicsGeneral MathematicsHomotopyMathematics::Optimization and ControlhomotopyproperComputer Science::Numerical AnalysisRegular homotopyCombinatoricsn-connectedPolyhedronEquivalence relationtucker propertySimplicial mapMathematics
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Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming

2008

AbstractThis paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.

Mathematical optimizationApplied MathematicsMathematics::Optimization and ControlEfficient frontierPortfolio selection problemSortino ratioFuzzy mathematical programmingRate of return on a portfolioComputational MathematicsDownside risk functionFuzzy returnsComputer Science::Computational Engineering Finance and ScienceReplicating portfolioCapital asset pricing modelPortfolioPortfolio optimizationSemi-infinite programmingModern portfolio theoryMathematicsJournal of Computational and Applied Mathematics
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Fuzzy portfolio selection based on the analysis of efficient frontiers

2011

We present an algorithm for analyzing the geometry of the efficient frontier of the portfolio selection problem with semicontinuous variable and cardinality constraints, and use it as a basis to solve a fuzzy version of the problem, designed to obtain efficient portfolios, in the Markowitz's sense, for which the trade-off between expected return and assumed risk fits better the investor's subjective criteria. We illustrate our proposal with an example solved with LINGO and Mathematica.

Mathematical optimizationCardinalityFuzzy setMathematics::Optimization and ControlPortfolioFuzzy numberFuzzy set operationsEfficient frontierStatistics::Other StatisticsPortfolio optimizationFuzzy logicMathematics2011 11th International Conference on Intelligent Systems Design and Applications
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Optimal control of option portfolios and applications

1999

We present an expected utility maximisation framework for optimally controlling a portfolio of options. By combining the replication approach to option pricing with ideas of the martingale approach to (stock) portfolio optimisation we arrive at an explicit solution of the option portfolio problem. Its characteristics are illustrated by some specific examples. As an application, we calculate an optimal option and consumption strategy for an investor who is obliged to hold a stock position until the time horizon.

Mathematical optimizationComputer scienceMathematics::Optimization and ControlTime horizonManagement Science and Operations ResearchOptimal controlMartingale (betting system)Computer Science::Computational Engineering Finance and ScienceValuation of optionsBusiness Management and Accounting (miscellaneous)PortfolioPosition (finance)Expected utility hypothesisStock (geology)OR Spectrum
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Necessary Optimality Conditions in Multiobjective Dynamic Optimization

2004

We consider a nonsmooth multiobjective optimal control problem related to a general preference. Both differential inclusion and endpoint constraints are involved. Necessary conditions and Hamiltonian necessary conditions expressed in terms of the limiting Frechet subdifferential are developed. Examples of useful preferences are given.

Mathematical optimizationControl and OptimizationDifferential inclusionApplied MathematicsMathematics::Optimization and ControlLimitingSubderivativeOptimal controlHamiltonian (control theory)MathematicsSIAM Journal on Control and Optimization
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Optimality conditions for nondifferentiable convex semi-infinite programming

1983

This paper gives characterizations of optimal solutions to the nondifferentiable convex semi-infinite programming problem, which involve the notion of Lagrangian saddlepoint. With the aim of giving the necessary conditions for optimality, local and global constraint qualifications are established. These constraint qualifications are based on the property of Farkas-Minkowski, which plays an important role in relation to certain systems obtained by linearizing the feasible set. It is proved that Slater's qualification implies those qualifications.

Mathematical optimizationGeneral MathematicsFeasible regionMathematics::Optimization and ControlRegular polygonConstraint satisfactionSemi-infinite programmingConstraint (information theory)Convex optimizationConstraint logic programmingComputer Science::Programming LanguagesConvex functionSoftwareMathematicsMathematical Programming
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Decision Making on Pareto Front Approximations with Inherent Nondominance

2011

t Approximating the Pareto fronts of nonlinear multiobjective optimization problems is considered and a property called inherent nondominance is proposed for such approximations. It is shown that an approximation having the above property can be explored by interactively solving a multiobjective optimization problem related to it. This exploration can be performed with available interactive multiobjective optimization methods. The ideas presented are especially useful in solving computationally expensive multiobjective optimization problems with costly function value evaluations. peerReviewed

Mathematical optimizationProperty (philosophy)Multiobjective OptimizationComputer Science::Neural and Evolutionary ComputationMathematicsofComputing_NUMERICALANALYSISMathematics::Optimization and ControlPareto principleFunction (mathematics)monitavoiteoptimointiComputingMethodologies_ARTIFICIALINTELLIGENCEMulti-objective optimizationMultiobjective optimization problemNonlinear systemPareto optimalObjective vectorMathematics
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The approximate subdifferential of composite functions

1993

This paper deals with the approximate subdifferential chain rule in a Banach space. It establishes specific results when the real-valued function is locally Lipschitzian and the mapping is strongly compactly Lipschitzian.

Mathematics::Functional AnalysisComputer Science::Systems and ControlGeneral MathematicsMathematical analysisComposite numberMathematics::Optimization and ControlBanach spaceApplied mathematicsFunction (mathematics)SubderivativeChain ruleMathematicsBulletin of the Australian Mathematical Society
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Qualification conditions for multivalued functions in Banach spaces with applications to nonsmooth vector optimization problems

1994

In this paper we introduce qualification conditions for multivalued functions in Banach spaces involving the A-approximate subdifferential, and we show that these conditions guarantee metric regularity of multivalued functions. The results are then applied for deriving Lagrange multipliers of Fritz—John type and Kuhn—Tucker type for infinite non-smooth vector optimization problems.

Mathematics::Functional AnalysisMathematical optimizationMultivalued functionGeneral MathematicsNumerical analysisMathematics::Optimization and ControlBanach spaceSubderivativeType (model theory)Physics::History of Physicssymbols.namesakeVector optimizationLagrange multiplierMetric (mathematics)symbolsApplied mathematicsSoftwareMathematicsMathematical Programming
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