Search results for " optimization."

showing 10 items of 2333 documents

On local optima in minimum time control of the restricted three-body problem

2016

International audience; The structure of local minima for time minimization in the controlled three-body problem is studied. Several homotopies are systematically used to unfold the structure of these local minimizers, and the resulting singularity of the path associated with the value function is analyzed numerically.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]0209 industrial biotechnologyMathematical optimizationHomotopyCircular restricted three body problemShooting Homotopy02 engineering and technologyMSC : 70F07 (49K15 49N90 58K99)Optimal controlThree-body problem01 natural sciencesOptimal controlMaxima and minimaSwallowtail singularity020901 industrial engineering & automationSingularityLocal optimumBellman equation0103 physical sciencesPath (graph theory)Applied mathematics[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]010303 astronomy & astrophysicsMathematics
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Regularization of chattering phenomena via bounded variation controls

2018

In control theory, the term chattering is used to refer to strong oscillations of controls, such as an infinite number of switchings over a compact interval of times. In this paper we focus on three typical occurences of chattering: the Fuller phenomenon, referring to situations where an optimal control switches an infinite number of times over a compact set; the Robbins phenomenon, concerning optimal control problems with state constraints, meaning that the optimal trajectory touches the boundary of the constraint set an infinite number of times over a compact time interval; the Zeno phenomenon, referring as well to an infinite number of switchings over a compact set, for hybrid optimal co…

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]0209 industrial biotechnologyState constraintsBoundary (topology)02 engineering and technologyInterval (mathematics)01 natural sciences020901 industrial engineering & automationShooting methodConvergence (routing)FOS: MathematicsApplied mathematicsHybrid problems0101 mathematicsElectrical and Electronic EngineeringMathematics - Optimization and ControlMathematicsTotal variation010102 general mathematics[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Optimal controlComputer Science ApplicationsControllabilityControl and Systems EngineeringOptimization and Control (math.OC)Chattering controlBounded variationTrajectory[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Fuller phenomenon
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Convergence rate of a relaxed inertial proximal algorithm for convex minimization

2018

International audience; In a Hilbert space setting, the authors recently introduced a general class of relaxed inertial proximal algorithms that aim to solve monotone inclusions. In this paper, we specialize this study in the case of non-smooth convex minimization problems. We obtain convergence rates for values which have similarities with the results based on the Nesterov accelerated gradient method. The joint adjustment of inertia, relaxation and proximal terms plays a central role. In doing so, we highlight inertial proximal algorithms that converge for general monotone inclusions, and which, in the case of convex minimization, give fast convergence rates of values in the worst case.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]Class (set theory)Control and OptimizationInertial frame of referenceLyapunov analysis0211 other engineering and technologies02 engineering and technologyManagement Science and Operations Research01 natural sciencessymbols.namesakenonsmooth convex minimizationrelaxationweak-convergence0101 mathematics[MATH]Mathematics [math]point algorithmMathematics021103 operations researchWeak convergence[QFIN]Quantitative Finance [q-fin]Applied MathematicsHilbert space[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]dynamicsmaximally monotone operatorsInertial proximal method010101 applied mathematicsMonotone polygonRate of convergenceConvex optimizationmaximal monotone-operatorssymbolsRelaxation (approximation)[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]subdifferential of convex functionsAlgorithm
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Time Versus Energy in the Averaged Optimal Coplanar Kepler Transfer towards Circular Orbits

2015

International audience; The aim of this note is to compare the averaged optimal coplanar transfer towards circular orbits when the costs are the transfer time transfer and the energy consumption. While the energy case leads to analyze a 2D Riemannian metric using the standard tools of Riemannian geometry (curvature computations, geodesic convexity), the time minimal case is associated to a Finsler metric which is not smooth. Nevertheless a qualitative analysis of the geodesic flow is given in this article to describe the optimal transfers. In particular we prove geodesic convexity of the elliptic domain.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]ComputationGeodesic convexity02 engineering and technologyRiemannian geometryCurvature01 natural sciencesDomain (mathematical analysis)Low thrust orbit transfersymbols.namesakeAveraging0203 mechanical engineeringFOS: MathematicsTime transferGeodesic convexityCircular orbit0101 mathematicsMathematics - Optimization and ControlMathematics020301 aerospace & aeronauticsApplied Mathematics010102 general mathematicsMathematical analysisOptimal controlOptimization and Control (math.OC)Metric (mathematics)symbolsRiemann-Finsler Geometry[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Mathematics::Differential Geometry
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Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation

2017

International audience; The goal of this paper is to show how non-parametric statistics can be used to solve some chance constrained optimization and optimal control problems. We use the Kernel Density Estimation method to approximate the probability density function of a random variable with unknown distribution , from a relatively small sample. We then show how this technique can be applied and implemented for a class of problems including the God-dard problem and the trajectory optimization of an Ariane 5-like launcher.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]Mathematical optimizationControl and Optimizationchance constrained optimizationKernel density estimation0211 other engineering and technologiesProbability density function02 engineering and technology01 natural sciencesKernel Density Estimation010104 statistics & probability0101 mathematicsMathematics021103 operations researchApplied MathematicsConstrained optimizationTrajectory optimizationstochastic optimizationOptimal controlOptimal controlDistribution (mathematics)Aerospace engineeringControl and Systems EngineeringStochastic optimization[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Random variableSoftware
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A combination of algebraic, geometric and numerical methods in the contrast problem by saturation in magnetic resonance imaging

2014

In this article, the contrast imaging problem by saturation in nuclear magnetic resonance is modeled as a Mayer problem in optimal control. The optimal solution can be found as an extremal solution of the Maximum Principle and analyzed with the recent advanced techniques of geometric optimal control. This leads to a numerical investigation based on shooting and continuation methods implemented in the HamPath software. The results are compared with a direct approach to the optimization problem and implemented within the Bocop toolbox. In complement lmi techniques are used to estimate a global optimum. It is completed with the analysis of the saturation problem of an ensemble of spin particle…

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]Moment optimization[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Direct methodContrast imaging in NMR[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Geometric optimal controlShooting and continuation techniques
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Minimum Time Control of the Restricted Three-Body Problem

2012

The minimum time control of the circular restricted three-body problem is considered. Controllability is proved on an adequate submanifold. Singularities of the extremal flow are studied by means of a stratification of the switching surface. Properties of homotopy maps in optimal control are framed in a simple case. The analysis is used to perform continuations on the two parameters of the problem: The ratio of the masses, and the magnitude of the control.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]Surface (mathematics)0209 industrial biotechnologyControl and OptimizationApplied MathematicsHomotopy010102 general mathematicsMathematical analysis[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]02 engineering and technologyThree-body problemOptimal controlSubmanifold01 natural sciencesControllability020901 industrial engineering & automationSimple (abstract algebra)Gravitational singularity[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]0101 mathematicsMathematicsSIAM Journal on Control and Optimization
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Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO

2016

This paper presents an improved wave kernel signature (WKS) using the modified particle swarm optimization (MPSO)-based intelligent recognition and matching on 3D shapes. We select the first feature vector from WKS, which represents the 3D shape over the first energy scale. The choice of this vector is to reinforce robustness against non-rigid 3D shapes. Furthermore, an optimized WKS-based method for extracting key-points from objects is introduced. Due to its discriminative power, the associated optimized WKS values with each point remain extremely stable, which allows for efficient salient features extraction. To assert our method regarding its robustness against topological deformations,…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO ] Computer Science [cs]Matching (graph theory)Feature vectorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[INFO] Computer Science [cs][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Kernel (linear algebra)[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Discriminative modelRobustness (computer science)0202 electrical engineering electronic engineering information engineeringFeature (machine learning)[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUSMathematicsbusiness.industryParticle swarm optimization[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognition020201 artificial intelligence & image processingArtificial intelligencebusinessEnergy (signal processing)
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Drivers-Inspired Ants for Solving the Vehicle Routing Problem with Time Windows

2016

International audience; In our study, we develop a method that merges two information sources within ants colony optimization heuristic. Namely artificial ants which occurs for short term optimization and transporter's vehicles that occurs in long term and continuous optimization toward solving the real-world vehicle routing problem. This study is supported by a transporter (Upsilon) of the region of l'Yonne in France and a transport and logistics software development company (Tedies). Our method suits for transporters that use human planners to make decisions about their tours and intending to move to computer planners without drastically upsetting the drivers habits. Hence, the pledge of …

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO ] Computer Science [cs]Operations researchComputer scienceHeuristic (computer science)0211 other engineering and technologies02 engineering and technology[INFO] Computer Science [cs]Pledge[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Software[ SPI.NRJ ] Engineering Sciences [physics]/Electric powerVehicle routing problem0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]SimulationContinuous optimization021103 operations researchbusiness.industryAnt colony optimization algorithms[SPI.NRJ]Engineering Sciences [physics]/Electric powerSoftware development[SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsTerm (time)020201 artificial intelligence & image processingbusiness[SPI.NRJ] Engineering Sciences [physics]/Electric power
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Scheduling independent stochastic tasks under deadline and budget constraints

2018

This article discusses scheduling strategies for the problem of maximizing the expected number of tasks that can be executed on a cloud platform within a given budget and under a deadline constraint. The execution times of tasks follow independent and identically distributed probability laws. The main questions are how many processors to enroll and whether and when to interrupt tasks that have been executing for some time. We provide complexity results and an asymptotically optimal strategy for the problem instance with discrete probability distributions and without deadline. We extend the latter strategy for the general case with continuous distributions and a deadline and we design an ef…

[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]Mathematical optimizationOperations researchComputer science[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Cloud computing[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technologyExpected valueTheoretical Computer ScienceScheduling (computing)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]deadline0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]schedulingComputer Science::Operating SystemsComputingMilieux_MISCELLANEOUSBudget constraint020203 distributed computingcloud platformindependent tasksbusiness.industry[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationstochastic costAsymptotically optimal algorithmContinuous distributions[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Hardware and ArchitectureProbability distribution[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]020201 artificial intelligence & image processingInterrupt[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessSoftwarebudget
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