Search results for "OPTIMA"

showing 10 items of 735 documents

Geometric optimal control of the contrast problem in Magnetic Resonance Imaging

2012

Abstract The control of the dynamics of spin systems by magnetic fields has opened intriguing possibilities in quantum computing and in Nuclear Magnetic Resonance spectroscopy. In this framework, optimal control theory has been used to design control fields able to realize a given task while minimizing a prescribed cost such as the energy of the field or the duration of the process. However, some of the powerful tools of optimal control had not been used yet for NMR applications in medical imagery. Here, we show that the geometric control theory approach can be advantageously combined with NMR methods to crucially optimize the imaging contrast. This approach is applied to a benchmark proble…

Mathematical optimizationField (physics)Process (computing)Benchmark (computing)General MedicineOptimal controlSingular controlAlgorithmEnergy (signal processing)MathematicsMagnetic fieldQuantum computerIFAC Proceedings Volumes
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Two-Sided Guaranteed Estimates of the Cost Functional for Optimal Control Problems with Elliptic State Equations

2014

In the paper, we discuss error estimation methods for optimal control problems with distributed control functions entering the right-hand side of the corresponding elliptic state equations. Our analysis is based on a posteriori error estimates of the functional type, which were derived in the last decade for many boundary value problems. They provide guaranteed two-sided bounds of approximation errors for any conforming approximation. If they are applied to approximate solutions of state equations, then we obtain new variational formulations of optimal control problems and guaranteed bounds of the cost functional. Moreover, for problems with linear state equations this procedure leads to gu…

Mathematical optimizationFunctional typeA priori and a posterioriBoundary value problemState (functional analysis)Control (linguistics)Optimal controlEstimation methodsMathematics
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NAUTILUS method: An interactive technique in multiobjective optimization based on the nadir point

2010

Most interactive methods developed for solving multiobjective optimization problems sequentially generate Pareto optimal or nondominated vectors and the decision maker must always allow impairment in at least one objective function to get a new solution. The NAUTILUS method proposed is based on the assumptions that past experiences affect decision makers’ hopes and that people do not react symmetrically to gains and losses. Therefore, some decision makers may prefer to start from the worst possible objective values and to improve every objective step by step according to their preferences. In NAUTILUS, starting from the nadir point, a solution is obtained at each iteration which dominates t…

Mathematical optimizationInformation Systems and ManagementInteractive programmingGeneral Computer Sciencebiologymedia_common.quotation_subjectManagement Science and Operations Researchbiology.organism_classificationMulti-objective optimizationIndustrial and Manufacturing EngineeringSightNegotiationIterated functionModeling and SimulationMinificationNautilusOptimal decisionMathematicsmedia_commonEuropean Journal of Operational Research
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Interactive Nonconvex Pareto Navigator for Multiobjective Optimization

2019

Abstract We introduce a new interactive multiobjective optimization method operating in the objective space called Nonconvex Pareto Navigator . It extends the Pareto Navigator method for nonconvex problems. An approximation of the Pareto optimal front in the objective space is first generated with the PAINT method using a relatively small set of Pareto optimal outcomes that is assumed to be given or computed prior to the interaction with the decision maker. The decision maker can then navigate on the approximation and direct the search for interesting regions in the objective space. In this way, the decision maker can conveniently learn about the interdependencies between the conflicting ob…

Mathematical optimizationInformation Systems and Managementinteractive multiobjective optimizationGeneral Computer ScienceComputer science0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchSpace (commercial competition)Multi-objective optimizationIndustrial and Manufacturing Engineering0502 economics and businessnonconvex problemsnavigationta113050210 logistics & transportation021103 operations researchpareto-tehokkuuspareto optimality05 social sciencesPareto principlemonitavoiteoptimointinavigointiModeling and Simulationmultiple objective programmingEuropean Journal of Operational Research
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Modelling energy storage systems using Fourier analysis: An application for smart grids optimal management

2014

In this paper, a new and efficient model for variables representation, named F-coding, in optimal power dispatch problems for smart electrical distribution grids is proposed. In particular, an application devoted to optimal energy dispatch of Distributed Energy Resources including ideal storage devices is here considered. Electrical energy storage systems, such as any other component that must meet an integral capacity constraint in optimal dispatch problems, have to show the same energy level at the beginning and at the end of the considered timeframe for operation. The use of zero-integral functions, such as sinusoidal functions, for the synthesis of the charge and discharge course of bat…

Mathematical optimizationIntegral constraintMulti-objective evolutionary algorithmbusiness.industryComputer scienceFourier analysiEconomic dispatchSmart gridsMulti-objective optimizationEnergy storageElectrical energy storage systemSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSettore ING-IND/31 - ElettrotecnicaSmart gridDistributed generationComponent (UML)Optimal dispatch of resourcebusinessRepresentation (mathematics)SoftwareEnergy (signal processing)Applied Soft Computing
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Determining the Difficulty of Landscapes by PageRank Centrality in Local Optima Networks

2016

The contribution of this study is twofold: First, we show that we can predict the performance of Iterated Local Search (ILS) in different landscapes with the help of Local Optima Networks (LONs) with escape edges. As a predictor, we use the PageRank Centrality of the global optimum. Escape edges can be extracted with lower effort than the edges used in a previous study. Second, we show that the PageRank vector of a LON can be used to predict the solution quality (average fitness) achievable by ILS in different landscapes.

Mathematical optimizationIterated local searchbusiness.industrymedia_common.quotation_subject02 engineering and technologyMachine learningcomputer.software_genreLocal optima networkslaw.inventionGlobal optimumPageRanklaw020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingQuality (business)Artificial intelligencebusinessCentralitycomputerMathematicsmedia_common
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Indirect Methods for Optimal Control Problems

2003

This chapter is dedicated to the numerical approximation of Optimal Control Problems. The algorithms are based on the necessary conditions for optimality which allow us to use a descent method for the minimization of the cost functional.

Mathematical optimizationNumerical approximationComputer scienceAdjoint equationMinificationOptimal controlDescent (mathematics)
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Multi-Start Methods

2006

Heuristic search procedures that aspire to find global optimal solutions to hard combinatorial optimization problems usually require some type of diversification to overcome local optimality. One way to achieve diversification is to re-start the procedure from a new solution once a region has been explored. In this chapter we describe the best known multi-start methods for solving optimization problems. We propose classifying these methods in terms of their use of randomization, memory and degree of rebuild. We also present a computational comparison of these methods on solving the linear ordering problem in terms of solution quality and diversification power.

Mathematical optimizationOptimization problemDegree (graph theory)Computer sciencemedia_common.quotation_subjectCombinatorial optimization problemQuality (business)Diversification (marketing strategy)Linear orderingGlobal optimalmedia_common
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An Interactive Evolutionary Multiobjective Optimization Method: Interactive WASF-GA

2015

In this paper, we describe an interactive evolutionary algorithm called Interactive WASF-GA to solve multiobjective optimization problems. This algorithm is based on a preference-based evolutionary multiobjective optimization algorithm called WASF-GA. In Interactive WASF-GA, a decision maker (DM) provides preference information at each iteration simple as a reference point consisting of desirable objective function values and the number of solutions to be compared. Using this information, the desired number of solutions are generated to represent the region of interest of the Pareto optimal front associated to the reference point given. Interactive WASF-GA implies a much lower computational…

Mathematical optimizationOptimization problemMultiobjective programmingComputer scienceEvolutionary algorithmReference point approachInteractive evolutionary computationPareto optimal solutionsEvolutionary algorithmsPreference (economics)AlgorithmMulti-objective optimizationInteractive methods
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Construction and optimality of a special class of balanced designs

2006

The use of balanced designs is generally advisable in experimental practice. In technological experiments, balanced designs optimize the exploitation of experimental resources, whereas in marketing research experiments they avoid erroneous conclusions caused by the misinterpretation of interviewed customers. In general, the balancing property assures the minimum variance of first-order effect estimates. In this work the authors consider situations in which all factors are categorical and minimum run size is required. In a symmetrical case, it is often possible to find an economical balanced design by means of algebraic methods. Conversely, in an asymmetrical case algebraic methods lead to e…

Mathematical optimizationOrthogonality (programming)Computer scienceHeuristic (computer science)Property (programming)Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaManagement Science and Operations Researchbalancingnearly orthogonalarraytwo- and three-level designsoptimalityEmpirical researchMinimum-variance unbiased estimatorEconometricsinteraction estimabilityAlgebraic numberSafety Risk Reliability and QualityMarketing researchCategorical variableasymmetrical (mixed-level) design
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