Search results for "Semi-infinite programming"

showing 10 items of 10 documents

An optimality test for semi-infinite linear programming

1992

In this paper we present a test to characterize the optimal solutions for the continuous semi-infinite linear programming problem. This optimality characterization is a condition of Kuhn–Tucker type. The resolution of a linear program permits to check the optimality of a feasible point,to detect the unboundedness of the problem and to find descent directions. We give some illustrative examples. We show that the local Mangasarian–Fromovitz constraint qualification is almost equivalent to Slater qualification for this problem. Furthermore, it follows from our study that this optimality condition is always necessary for a wide class of semi-infinite linear programming problems

Constraint (information theory)Mathematical optimizationControl and OptimizationLinear programmingSemi-infiniteApplied MathematicsPoint (geometry)Management Science and Operations ResearchType (model theory)Semi-infinite programmingLinear-fractional programmingDescent (mathematics)MathematicsOptimization
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Farkas-Minkowski systems in semi-infinite programming

1981

The Farkas-Minkowski systems are characterized through a convex cone associated to the system, and some sufficient conditions are given that guarantee the mentioned property. The role of such systems in semi-infinite programming is studied in the linear case by means of the duality, and, in the nonlinear case, in connection with optimality conditions. In the last case the property appears as a constraint qualification.

Discrete mathematicsPure mathematicsNonlinear systemControl and OptimizationApplied MathematicsMinkowski spaceSecond-order cone programmingDuality (optimization)Constraint satisfactionSemi-infinite programmingMathematicsApplied Mathematics & Optimization
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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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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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A purification algorithm for semi-infinite programming

1992

Abstract In this paper we present a purification algorithm for semi-infinite linear programming. Starting with a feasible point, the algorithm either finds an improved extreme point or concludes with the unboundedness of the problem. The method is based on the solution of a sequence of linear programming problems. The study of some recession conditions has allowed us to establish a weak assumption for the finite convergence of this algorithm. Numerical results illustrating the method are given.

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceLinear programmingManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringSemi-infinite programmingLinear-fractional programmingSimplex algorithmModeling and SimulationAlgorithm designCriss-cross algorithmExtreme pointAlgorithmGradient methodMathematicsEuropean Journal of Operational Research
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Optimization under Uncertainty and Linear Semi-Infinite Programming: A Survey

2001

This paper deals with the relationship between semi-infinite linear programming and decision making under uncertainty in imprecise environments. Actually, we have reviewed several set-inclusive constrained models and some fuzzy programming problems in order to see if they can be solved by means of a linear semi-infinite program. Finally, we present some numerical examples obtained by using a primal semi-infinite programming method.

Mathematical optimizationLinear programmingComputer scienceProbabilistic-based design optimizationComputer Science::Programming LanguagesFuzzy numberRobust optimizationSensitivity analysisStochastic programmingSemi-infinite programmingMembership function
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Solving a class of fuzzy linear programs by using semi-infinite programming techniques

2004

This paper deals with a class of Fuzzy Linear Programming problems characterized by the fact that the coefficients in the constraints are modeled as LR-fuzzy numbers with different shapes. Solving such problems is usually more complicated than finding a solution when all the fuzzy coefficients have the same shape. We propose a primal semi-infinite algorithm as a valuable tool for solving this class of Fuzzy Linear programs and, we illustrate it by means of several examples.

Mathematical optimizationLinear programmingMathematics::General MathematicsArtificial IntelligenceLogicFuzzy setFuzzy numberFuzzy set operationsFuzzy control systemDefuzzificationFuzzy logicSemi-infinite programmingMathematicsFuzzy Sets and Systems
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New descent rules for solving the linear semi-infinite programming problem

1994

The algorithm described in this paper approaches the optimal solution of a continuous semi-infinite linear programming problem through a sequence of basic feasible solutions. The descent rules that we present for the improvement step are quite different when one deals with non-degenerate or degenerate extreme points. For the non-degenerate case we use a simplex-type approach, and for the other case a search direction scheme is applied. Some numerical examples illustrating the method are given.

Scheme (programming language)Mathematical optimizationSequenceLinear programmingApplied MathematicsDegenerate energy levelsMathematicsofComputing_NUMERICALANALYSISManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringSemi-infinite programmingBasic solutionExtreme pointcomputerSoftwareDescent (mathematics)Mathematicscomputer.programming_languageOperations Research Letters
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A multi-local optimization algorithm

1998

The development of efficient algorithms that provide all the local minima of a function is crucial to solve certain subproblems in many optimization methods. A “multi-local” optimization procedure using inexact line searches is presented, and numerical experiments are also reported. An application of the method to a semi-infinite programming procedure is included.

Statistics and ProbabilityContinuous optimizationMathematical optimizationInformation Systems and ManagementMeta-optimizationManagement Science and Operations ResearchSemi-infinite programmingMaxima and minimaVector optimizationModeling and SimulationDiscrete Mathematics and CombinatoricsRandom optimizationMulti-swarm optimizationAlgorithmMetaheuristicMathematicsTop
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An overview of semi-infinite programming theory and related topics through a generalization of the alternative theorems

1984

We propose new alternative theorems for convex infinite systems which constitute the generalization of the corresponding toGale, Farkas, Gordan andMotzkin. By means of these powerful results we establish new approaches to the Theory of Infinite Linear Inequality Systems, Perfect Duality, Semi-infinite Games and Optimality Theory for non-differentiable convex Semi-Infinite Programming Problem.

TheoryofComputation_MISCELLANEOUSStatistics and ProbabilityConvex analysisDiscrete mathematicsGeneralizationLinear matrix inequalityRegular polygonDuality (optimization)Optimality theorySemi-infinite programmingAlgebraLinear inequalityTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESStatistics Probability and UncertaintyMathematicsTrabajos de Estadistica y de Investigacion Operativa
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