Search results for "optimaalisuus"

showing 6 items of 6 documents

Optimal transport maps on Alexandrov spaces revisited

2018

We give an alternative proof for the fact that in $n$-dimensional Alexandrov spaces with curvature bounded below there exists a unique optimal transport plan from any purely $(n-1)$-unrectifiable starting measure, and that this plan is induced by an optimal map.

Mathematics - Differential GeometryClass (set theory)Pure mathematicsGeneral MathematicsExistential quantificationPlan (drawing)Algebraic geometryoptimaalisuusCurvatureMeasure (mathematics)Primary 53C23. Secondary 49K30Mathematics - Analysis of PDEsMathematics - Metric GeometryFOS: Mathematicsmass transportationMathematics::Metric GeometryMathematicsAlexandrov-avaruudetMetric Geometry (math.MG)Number theoryDifferential Geometry (math.DG)Bounded functionMathematics::Differential GeometrymassasiirtoAlexandrov spacesAnalysis of PDEs (math.AP)
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A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution

2011

Differential evolution has become one of the most widely used evolution- ary algorithms in multiobjective optimization. Its linear mutation operator is a sim- ple and powerful mechanism to generate trial vectors. However, the performance of the mutation operator can be improved by including a nonlinear part. In this pa- per, we propose a new hybrid mutation operator consisting of a polynomial based operator with nonlinear curve tracking capabilities and the differential evolution’s original mutation operator, to be efficiently able to handle various interdependencies between decision variables. The resulting hybrid operator is straightforward to implement and can be used within most evoluti…

Pareto optimalityMathematical optimizationEvolutionary algorithmComputational intelligenceMOEA/DNonlinearGenetic operatorEvolutionary algorithmsMulti-objective optimizationPolynomialTheoretical Computer ScienceDEOperator (computer programming)Evolutionary algorithms; DE; Nonlinear; Multi-criteria optimization; Polynomial; Pareto optimality; MOEA/DPareto-optimaalisuusMathematicsMatematikMulti-criteria optimizationState (functional analysis)monitavoiteoptimointiNonlinear systemDifferential evolutionGeometry and TopologyAlgorithmSoftwareMathematics
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PAINT : Pareto front interpolation for nonlinear multiobjective optimization

2011

A method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem. When the scalarizations of the interactive method used do not introduce nonlinearity to the problem (which is true e.g., for the synchronous NIMBUS method), the scalarizations of the surrogate problem can be optimized with available mixed integer linear solvers. Thus, the use of the interactive meth…

Pareto optimalityMathematical optimizationMatematikControl and OptimizationApplied MathematicsComputationally expensive problemsMulti-objective optimizationmonitavoiteoptimointiSet (abstract data type)Computational MathematicsPareto optimalNonlinear systemMultiobjective optimization problemapproksimaatioPareto-optimaalisuusapproksimointiAlgorithmApproximationMathematicsInterpolationMathematicsInteger (computer science)Multiobjective optimizationInteractive decision making
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Efficient design and modeling strategies for follow-up studies with time-varying covariates

2015

Epidemiological studies can often be designed in several ways, some of which may be more optimal than others. Possible designs may differ in the required resources or the ability to provide reliable answers to the questions under study. In addition, once the data are collected, the selected modeling approach may affect how efficiently the data are utilized. The purpose of this dissertation is to investigate efficient designs and analysis meth ods in follow-up studies with longitudinal measurements. A key question is how to select optimally a subcohort for a new longitudinal covariate measurement if we cannot afford to measure the entire cohort. Another key question we consider is how to determine …

kuolleisuustime-varying covariatesdata collectionkustannustehokkuusanalyysimenetelmätennusteetfollow-up studypitkittäistutkimusoptimaalisuusrisk predictiondataaikariippuvat kovariaatitSeurantatutkimustutkimusmenetelmätsydän- ja verisuonitauditcardiovascular disease mortalitylongitudinal measurementssimulointioptimal designepidemiologiakohorttitutkimustutkimusaineistoterveysriskit
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Multi-scenario multi-objective robust optimization under deep uncertainty: A posteriori approach

2021

This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results obtained with the novel approach to those obtained with previously used approaches. We show that the novel approach guarantees the feasibility and robust efficiency of the produced solutions under all selected scenarios, while decreasing computation cost, addresses the scenario-dependency issues, and enables the decision-makers to explore the trade-off …

Mathematical optimizationEnvironmental Engineering010504 meteorology & atmospheric sciencesComputer sciencepäätöksentekotehokkuus0211 other engineering and technologies02 engineering and technologyoptimaalisuus01 natural sciencesMulti-objective optimizationScenario planningRobust decision-makingdeep uncertaintyoptimointiRobustness (computer science)Reference pointsScenario planning0105 earth and related environmental sciencesscenario planningrobust decision making scalarizing functions021103 operations researchpareto-tehokkuusEcological ModelingPareto principleRobust optimizationskenaariotepävarmuusmonitavoiteoptimointireference pointsMulti-objective optimizationRobust decision making scalarizing functionsmulti-objective optimizationDeep uncertaintyBenchmark (computing)A priori and a posterioriSoftware
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Why Use Interactive Multi-Objective Optimization in Chemical Process Design?

2008

Problems in chemical engineering, like most real-world optimization problems, typically, have several conflicting performance criteria or objectives and they often are computationally demanding, which sets special requirements on the optimization methods used. In this chapter, we point out some shortcomings of some widely used basic methods of multi-objective optimization. As an alternative, we suggest using interactive approaches where the role of a decision maker or a designer is emphasized. Interactive multi-objective optimization has been shown to suit well for chemical process design problems because it takes the preferences of the decision maker into account in an iterative manner tha…

scalarizationPareto optimalityOptimization problemComputer scienceCompromisemedia_common.quotation_subjectProcess designcomputer.software_genreUSableMulti-objective optimizationMultiple criteria decision making (MCDM)Conflicting objectiveskemian tekniikkaPareto-optimaalisuusMonitavoitteinen päätöksenteko (MCDM)media_commonPoint (typography)Multimediainteraktiiviset menetelmätInformation and Computer Scienceskalarisointiinteractive methodsIndustrial engineeringmonitavoitteinen päätöksentekochemical engineeringcomputer
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