Search results for "Mathematical optimization"

showing 10 items of 1300 documents

An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems

2015

This paper presents a new preference based interactive evolutionary algorithm (I-SIBEA) for solving multiobjective optimization problems using weighted hypervolume. Here the decision maker iteratively provides her/his preference information in the form of identifying preferred and/or non-preferred solutions from a set of nondominated solutions. This preference information provided by the decision maker is used to assign weights of the weighted hypervolume calculation to solutions in subsequent generations. In any generation, the weighted hypervolume is calculated and solutions are selected to the next generation based on their contribution to the weighted hypervolume. The algorithm is compa…

Flexibility (engineering)Set (abstract data type)Mathematical optimizationComputer scienceBenchmark (computing)Evolutionary algorithmmultiobjective optimizationInteractive evolutionary computationevolutionary algorithmsinteractive methodsMulti-objective optimizationEvolutionary programmingPreference
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Optimization of Long-Run Average-Flow Cost in Networks With Time-Varying Unknown Demand

2010

We consider continuous-time robust network flows with capacity constraints and unknown but bounded time-varying demand. The problem of interest is to design a control strategy off-line with no knowledge of the demand realization. Such a control strategy regulates the flow on-line as a function of the realized demand. We address both the case of systems without and with buffers. The main novelty in this work is that we consider a convex cost which is a function of the long-run average-flow and average-demand. We distinguish a worst-case scenario where the demand is the worst-one from a deterministic scenario where the demand has a neutral behavior. The resulting strategies are called min-max…

Flow control (data)Mathematical optimizationComputer scienceTime varying systemsFunction (mathematics)Optimal controlFlow networkMin-max optimalityAverage flow cost; Flow control; Gradient-based control; Min-max optimality; Uncertain demand; Time varying systems; Time varying networksComputer Science ApplicationsAverage flow costFlow controlControl and Systems EngineeringRobustness (computer science)Control theoryBounded functionProduction controlElectrical and Electronic EngineeringTime varying networksAverage flow cost flow control gradient-based control min-max optimality uncertain demandGradient-based controlAverage costUncertain demand
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Objective function design for robust optimality of linear control under state-constraints and uncertainty

2009

We consider a model for the control of a linear network flow system with unknown but bounded demand and polytopic bounds on controlled flows. We are interested in the problem of finding a suitable objective function that makes robust optimal the policy represented by the so-called linear saturated feedback control. We regard the problem as a suitable differential game with switching cost and study it in the framework of the viscosity solutions theory for Bellman and Isaacs equations. © 2009 EDP Sciences, SMAI.

Flow control (data)Mathematical optimizationControl and OptimizationControl (management)State (functional analysis)Optimal control viscosity solutions differential games switching flow control networksOptimal controlComputational MathematicsControl and Systems EngineeringControl theoryViscosity (programming)Bounded functionDifferential gameMathematicsLinear control
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A decentralized solution for the constrained minimum cost flow

2010

In this paper we propose a decentralized solution to the problem of network stabilization, under flow constraints ensuring steady—state flow optimality. We propose a stabilizing strategy for network flow control with capacity constraints which drives the buffer levels arbitrarily close to a desired reference. This is a decentralized strategy optimizing the flow via the minimization of a quadratic cost of the control. A second problem characterized by non-fully connected networks is also considered, for which an exact network equilibrium is not possible. Here, the strategy, in the absence of constraints leads to a least square decentralized problem, but, unfortunately, in the presence of con…

Flow control (data)Mathematical optimizationnetworks; control; optimizaton; decentralizedEthernet flow controlnetworks control optimizaton decentralizedoptimizatonOptimal controlMulti-commodity flow problemSettore ING-INF/04 - AutomaticaControl theoryRobustness (computer science)networksdecentralizedMinimum-cost flow problemQuadratic programmingMinificationSettore MAT/09 - Ricerca OperativacontrolMathematics49th IEEE Conference on Decision and Control (CDC)
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Denoising of MR spectroscopy signals using total variation and iterative Gauss-Seidel gradient updates

2015

We present a fast variational approach for denoising signals from magnetic resonance spectroscopy (MRS). Differently from the TV approaches applied to denoising of images, this is the first time to our knowledge that it has been used for the processing of free induction decay signals from single-voxel spectroscopy (SVS) acquisitions. Another novelty in this study is the direct use of the Euler Lagrange formulation coupled with Gauss Seidel gradient updates to improve the speed of iteration and reduce ringing. Results from brain MRS signals show improvement in signal to noise ratio as well as reduction in estimation error in the quantification of metabolites.

Free induction decayReduction (complexity)Mathematical optimizationSignal-to-noise ratioNoise reductionGauss–Seidel methodRingingTotal variation denoisingSpectroscopyAlgorithmMathematics2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)
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Model of a Constructive Fuctional Optimization of the Cardan Cross

2015

This paper aims to establish an optimization model using the Ansys program, and taking into account the specific constraints depending on the functional role of the specific area. We present certain calculation parameters applied to the cardanic transmission of the Dacia, this cardanic transmission being considered an optimization model. The entire cardanic transmission was analyzed, resulting that the cardan crosses are parts which are strained the most, and that is why it will be here that the optimization will be focused, in terms of minimizing the Von Mises stress.

Functional roleEngineeringMathematical optimizationTransmission (telecommunications)business.industryNumerical analysisvon Mises yield criterionGeneral MedicinebusinessConstructiveApplied Mechanics and Materials
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Optimization Under Fuzzy Max-t-Norm Relation Constraints

2019

Fuzzy relation equations and inequalities play an important role in many tools of fuzzy modelling and have been extensively studied. In many practical applications they are used as constraints in optimization. Algorithms for specific objective functions have been proposed by many authors. In this paper we introduce a method to convert a system of fuzzy relation constraints with max-t-norm composition to a linear constraint system by adding integer variables. A numerical example is provided to illustrate the proposed method.

Fuzzy modellingConstraint (information theory)Mathematical optimizationRelation (database)Mathematics::Metric GeometryT-normComposition (combinatorics)Fuzzy logicMathematicsInteger (computer science)
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Improving the energy efficiency of an islanded distribution network using classical and innovative computation methods

2016

The paper presents the analysis of some potentially suitable actions for reducing the energy losses of an islanded Medium Voltage distribution network, with the aim of improving electricity distribution efficiency. For this purpose, four actions are considered: 1) increasing the network's rated voltage; 2) reactive power compensation through static capacitor banks; 3) reactive power compensation through switchable capacitor banks; 4) installation of distributed photovoltaic (PV) generation. The first two measures are typically taken into account by the distribution system operators and can be examined by means of classical design methods, whereas the latter two more innovative actions are t…

GHG emissionEngineeringMathematical optimizationOptimization problemSociology and Political Science020209 energy02 engineering and technology010501 environmental sciencesManagement Monitoring Policy and LawDevelopment01 natural sciencesCompensation (engineering)law.inventionlawSustainable development0202 electrical engineering electronic engineering information engineeringDevelopment3304 EducationBusiness and International ManagementDesign methods0105 earth and related environmental sciencesElectric power distributionbusiness.industryPhotovoltaic systemElectrical engineeringAC powerSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaCapacitorEnergy efficiencybusinessLawEfficient energy useUtilities Policy
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Split Bregman Method for Gravitational Wave Denoising

2014

This paper presents a progress report in our aim to develop a Total Variation algorithm for denoising of gravitational waves. These algorithms, are routinely employed in the context of image processing and they do not need any a priori information on the signals. We apply our method to two different types of numerically-simulated gravitational wave signals, namely burst produced from the core collapse of rotating stars and waveforms from binary black hole mergers, and present a preliminary assessment of its capabilities.

General Relativity and Quantum CosmologyMathematical optimizationBregman methodBinary black holeGravitational waveComputer scienceNoise reductionA priori and a posterioriWaveformImage processingContext (language use)Algorithm
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NUMERICAL ALGORITHMS

2013

For many systems of differential equations modeling problems in science and engineering, there are natural splittings of the right hand side into two parts, one non-stiff or mildly stiff, and the other one stiff. For such systems implicit-explicit (IMEX) integration combines an explicit scheme for the non-stiff part with an implicit scheme for the stiff part. In a recent series of papers two of the authors (Sandu and Zhang) have developed IMEX GLMs, a family of implicit-explicit schemes based on general linear methods. It has been shown that, due to their high stage order, IMEX GLMs require no additional coupling order conditions, and are not marred by order reduction. This work develops a …

General linear methodsMathematical optimizationIMEX methods; general linear methods; error analysis; order conditions; stability analysisIMEX methodsDifferential equationSCHEMESorder conditionsMathematics AppliedExtrapolationStability (learning theory)QUADRATIC STABILITYstability analysisPARABOLIC EQUATIONSSYSTEMSNORDSIECK METHODSFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisRUNGE-KUTTA METHODSMULTISTEP METHODSerror analysisMathematicsCONSTRUCTIONSeries (mathematics)Applied MathematicsNumerical analysisComputer Science - Numerical AnalysisStability analysisORDEROrder conditionsNumerical Analysis (math.NA)Computer Science::Numerical AnalysisRunge–Kutta methodsGeneral linear methodsError analysisORDINARY DIFFERENTIAL-EQUATIONSOrdinary differential equationgeneral linear methodsMathematics
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