Search results for "optimization"

showing 10 items of 2824 documents

Recherche Tabou Robuste pour l'allocation de fréquences

2014

National audience; 1. Problématique : depuis le démarrage des réseaux cellulaires (2G, 3G, 3.5G), les opérateurs configuraient manuellement la gestion des paramètres réseau. Avec l'apparition des réseaux 4G/LTE, la notion de Self-Organizing Network (SON) a vu le jour. Les SON introduisent des fonctions avancées de paramétrage automatique du réseau en fonction de la demande. Grâce à cette technologie, les opérateurs peuvent désormais améliorer la flexibilité et les performances du réseau en réduisant les coûts d'exploitation. Notre objectif est de proposer des solutions algorithmiques pouvant s'appliquer au SON. 2. Méthodologie : le problème d'allocation de fréquences est NP-difficile car il…

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]optimisation[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC][MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]algorithme tabouSONscénariosrobustesse
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One-parameter family of Clairaut-Liouville metrics

2007

Riemannian metrics with singularities are considered on the $2$-sphere of revolution. The analysis of such singularities is motivated by examples stemming from mechanics and related to projections of higher dimensional (regular) sub-Riemannian distributions. An unfolding of the metrics in the form of an homotopy from the canonical metric on $\SS^2$ is defined which allows to analyze the singular case as a limit of standard Riemannian ones. A bifurcation of the conjugate locus for points on the singularity is finally exhibited.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]space mechanics49K15 53C20 70Q05$2$-sphere of revolution[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC][MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Mathematics::Differential Geometryunfolding
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Intern conflicts and a production function with combining sub-factors

1994

Considering sub-factors, like different categories of capital or different categories of work, a production function is proposed: each sub-factor of one factor may be combined with each sub-factor of the other factor. Different types of programs exists at different levels. The conditions to obtain identical solution for these programs are studied. Considering that there is one responsible manager by program, conflicts between managers of each program arepossible because these programs give non identical solutions in general. The important fact is that these intern conflicts appear naturally without extra economical considerations

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]statisticsautomatiqueconflictfirmoperational researchfactor of production[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]control theoryoperations researchrecherche opérationnelle
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Sub-Riemannian geometry: one-parameter deformation of the Martinet flat case

1998

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]sub-Riemannian geometrysub-Riemannian sphere and distanceabnormal geodesics[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC][MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]ddc:510
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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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Kernel Density Estimation applied to the chance-constrained Goddard problem

2016

[INFO.INFO-NA] Computer Science [cs]/Numerical Analysis [cs.NA][MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]
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Optimisation d’un lanceur

2015

[INFO.INFO-NA] Computer Science [cs]/Numerical Analysis [cs.NA][MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]
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Robust control of networks under discrete disturbances and controls

2011

We consider dynamic networks where the disturbances and control actions take discrete values. We briefly survey some of our recent results establishing necessary and sufficient conditions for the existence of robustly globally invariant (hyper box) sets, as well as sufficient conditions for global attractivity of such sets.We then establish connections between these results and existing results in the literature for the setup where all the inputs are analog. Finally, we derive tight upper and lower bounds on the smallest such set in the special case of a degenerate network.

[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI]control and optimization
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