Search results for "Computer Science Application"

showing 10 items of 3998 documents

PAINT–SiCon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization

2014

We introduce a novel approximation method for multiobjective optimization problems called PAINT–SiCon. The method can construct consistent parametric representations of Pareto sets, especially for nonconvex problems, by interpolating between nondominated solutions of a given sampling both in the decision and objective space. The proposed method is especially advantageous in computationally expensive cases, since the parametric representation of the Pareto set can be used as an inexpensive surrogate for the original problem during the decision making process. peerReviewed

Mathematical optimizationControl and OptimizationApplied MathematicsMathematicsofComputing_NUMERICALANALYSISPareto principleSampling (statistics)Management Science and Operations ResearchSpace (mathematics)Multi-objective optimizationComputer Science ApplicationsNonlinear programmingSet (abstract data type)piecewise linear approximationmultiple criteria programmingnonlinear programmingRepresentation (mathematics)Parametric statisticsMathematicsJournal of Global Optimization
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A new preference handling technique for interactive multiobjective optimization without trading-off

2015

Because the purpose of multiobjective optimization methods is to optimize conflicting objectives simultaneously, they mainly focus on Pareto optimal solutions, where improvement with respect to some objective is only possible by allowing some other objective(s) to impair. Bringing this idea into practice requires the decision maker to think in terms of trading-off, which may limit the ability of effective problem solving. We outline some drawbacks of this and exploit another idea emphasizing the possibility of simultaneous improvement of all objectives. Based on this idea, we propose a technique for handling decision maker’s preferences, which eliminates the necessity to think in terms of t…

Mathematical optimizationControl and OptimizationExploitComputer scienceApplied Mathematicsmedia_common.quotation_subjectpreference informationPreference handlinginteractive methodsManagement Science and Operations ResearchDecision makerMulti-objective optimizationnegotiation supportComputer Science ApplicationsPareto optimalNegotiationmultiple objectivesNAUTILUS methodLimit (mathematics)Focus (optics)media_commonJournal of Global Optimization
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Functional A Posteriori Error Estimates for Time-Periodic Parabolic Optimal Control Problems

2015

This article is devoted to the a posteriori error analysis of multiharmonic finite element approximations to distributed optimal control problems with time-periodic state equations of parabolic type. We derive a posteriori estimates of the functional type, which are easily computable and provide guaranteed upper bounds for the state and co-state errors as well as for the cost functional. These theoretical results are confirmed by several numerical tests that show high efficiency of the a posteriori error bounds. peerReviewed

Mathematical optimizationControl and OptimizationMathematicsofComputing_NUMERICALANALYSISFinite element approximations010103 numerical & computational mathematicsType (model theory)01 natural sciencesparabolic time-periodic optimal control problemsError analysisFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisNumerical testsfunctional a posteriori error estimates0101 mathematicsMathematics - Optimization and Control49N20 35Q61 65M60 65F08Mathematicsta113Time periodicta111Numerical Analysis (math.NA)State (functional analysis)Optimal controlComputer Science Applications010101 applied mathematicsOptimization and Control (math.OC)multiharmonic finite element methodsSignal ProcessingA priori and a posterioriAnalysisNumerical Functional Analysis and Optimization
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Error Estimates for a Class of Elliptic Optimal Control Problems

2016

In this article, functional type a posteriori error estimates are presented for a certain class of optimal control problems with elliptic partial differential equation constraints. It is assumed that in the cost functional the state is measured in terms of the energy norm generated by the state equation. The functional a posteriori error estimates developed by Repin in the late 1990s are applied to estimate the cost function value from both sides without requiring the exact solution of the state equation. Moreover, a lower bound for the minimal cost functional value is derived. A meaningful error quantity coinciding with the gap between the cost functional values of an arbitrary admissible …

Mathematical optimizationControl and OptimizationNumerical analysis010102 general mathematicsta111010103 numerical & computational mathematicsOptimal control01 natural sciencesUpper and lower boundsComputer Science ApplicationsExact solutions in general relativityElliptic partial differential equationerror estimatesNorm (mathematics)Signal ProcessingA priori and a posterioriNumerical testselliptic optimal control problems0101 mathematicsAnalysisMathematics
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Reliability-based design optimization of trusses under dynamic shakedown constraints

2019

A reliability-based design optimization problem under dynamic shakedown constraints for elastic perfectly plastic truss structures subjected to stochastic wind actions is presented. The simultaneous presence of quasi-static (cyclic) thermal loads is also considered. As usual in the shakedown theory, the quasi-statical loads will be defined as variable within a deterministic domain, while the dynamic problem will be treated considering an extended Ceradini-Gavarini approach. Some sources of uncertainties are introduced in the structural system and in the load definition. The reliability-optimization problem is formulated as the minimization of the volume of the structure subjected to determi…

Mathematical optimizationControl and OptimizationOptimization problemComputer scienceMonte Carlo methodStructural system0211 other engineering and technologiesTruss02 engineering and technology0203 mechanical engineeringDynamic problemReliability-based designDynamic shakedownReliability (statistics)021106 design practice & managementElastic plastic trusseProbabilistic logicComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignComputer Science ApplicationsShakedown020303 mechanical engineering & transportsControl and Systems EngineeringSettore ICAR/08 - Scienza Delle CostruzioniSoftwareStochastic wind loadStructural and Multidisciplinary Optimization
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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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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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