Search results for "Mathematical optimization"

showing 10 items of 1300 documents

Explicit recursivity into reproducing kernel Hilbert spaces

2011

This paper presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces (RKHS). Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define model recursivity in the Hilbert space. The method exploits some properties of functional analysis and recursive computation of dot products without the need of pre-imaging. We illustrate the feasibility of the methodology in the particular case of the gamma-filter, an infinite impulse response (IIR) filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and electroencephalographic time se…

Mathematical optimizationgamma filterHilbert spaceDot productFilter (signal processing)pre-imagefunctional analysissymbols.namesakekernel methodsKernel methodKernel (statistics)symbolsRecursive filterInfinite impulse responseAlgorithmMathematicsReproducing kernel Hilbert spaceRecursive filter
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An IMEX-Scheme for Pricing Options under Stochastic Volatility Models with Jumps

2014

Partial integro-differential equation (PIDE) formulations are often preferable for pricing options under models with stochastic volatility and jumps, especially for American-style option contracts. We consider the pricing of options under such models, namely the Bates model and the so-called stochastic volatility with contemporaneous jumps (SVCJ) model. The nonlocality of the jump terms in these models leads to matrices with full matrix blocks. Standard discretization methods are not viable directly since they would require the inversion of such a matrix. Instead, we adopt a two-step implicit-explicit (IMEX) time discretization scheme, the IMEX-CNAB scheme, where the jump term is treated ex…

Mathematical optimizationimplicit-explicit time discretizationDiscretizationStochastic volatilityApplied Mathematicsta111Linear systemLU decompositionMathematics::Numerical Analysislaw.inventionComputational MathematicsMatrix (mathematics)stochastic volatility modelMultigrid methodlawValuation of optionsjump-diffusion modelJumpoption pricingfinite difference methodMathematicsSIAM Journal on Scientific Computing
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Optimal Placement of Pressure Sensors Using Fuzzy DEMATEL-Based Sensor Influence

2020

[EN] Nowadays, optimal sensor placement (OSP) for leakage detection in water distribution networks is a lively field of research, and a challenge for water utilities in terms of network control, management, and maintenance. How many sensors to install and where to install them are crucial decisions to make for those utilities to reach a trade-off between efficiency and economy. In this paper, we address the where-to-install-them part of the OSP through the following elements: nodes' sensitivity to leakage, uncertainty of information, and redundancy through conditional entropy maximisation. We evaluate relationships among candidate sensors in a network to get a picture of the mutual influenc…

Mathematical optimizationlcsh:Hydraulic engineeringDistribution networksoptimal sensor placementComputer scienceEntropyleakageGeography Planning and Development09.- Desarrollar infraestructuras resilientes promover la industrialización inclusiva y sostenible y fomentar la innovación0207 environmental engineeringDEMATEL02 engineering and technologyAquatic ScienceBiochemistryFuzzy logiclcsh:Water supply for domestic and industrial purposesSensitivityMulti-criteria decision-makingFuzzy dematellcsh:TC1-9780202 electrical engineering electronic engineering information engineeringmulti-criteria decision-makingEntropy (information theory)uncertainty020701 environmental engineeringMutual influenceWater Science and TechnologyConditional entropylcsh:TD201-500Network controlUncertaintyWater distribution networksensitivityPressure sensorOptimal sensor placementwater distribution network020201 artificial intelligence & image processingMATEMATICA APLICADAentropyLeakageWater
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Calculation of cost-optimal combination of building materials and technical systems for nZEB single-family house using global cost calculation method

2019

As a rule, during the design stage of a single-family house, only initial costs are taken into account and optimised. Long-term financial calculations are usually not even made. At the same time, total costs to design, build and operate the building show a real difference in expenses while living in this house. In the case of nearly zero energy buildings (nZEBs), this global cost approach becomes especially useful because of the strict requirements of heating and primary energy, as well as the compulsory use of renewable energy sources, requiring more detailed and comprehensive calculations of a cost-optimal set of solutions. In this study, a nZEB single-family house is analysed in detail u…

Mathematical optimizationlcsh:TA1-2040Computer scienceSingle-family detached homeTechnical systemsOptimal combinationlcsh:Engineering (General). Civil engineering (General)Cost calculationMATEC Web of Conferences
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Statistical methods for determining components non-liniarities, from thermoluminescent devices

2016

Thermoluminescent (TLD) dosimeters enjoy wide usage due to low cost and simplicity of use. They have however large errors at high doses in mixed-radiation fields, where non-linear effects occur. Algorithms based on the Akaike criterion [1] are presented for determining the maximal (physically meaningful) polynomial order with which the non-linearities are modeled. This depends on the number of points existing on a curve and on the points' errors.

Mathematical optimizationmedia_common.quotation_subjectPhysics::Medical PhysicsPolynomial order02 engineering and technology021001 nanoscience & nanotechnology01 natural sciencesThermoluminescence0103 physical sciencesAkaike criterionHigh dosesThermoluminescent dosimeterSimplicity010306 general physics0210 nano-technologyAlgorithmmedia_commonMathematics2016 IEEE 22nd International Symposium for Design and Technology in Electronic Packaging (SIITME)
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New Results on the Mixed General Routing Problem

2005

[EN] In this paper, we deal with the polyhedral description and the resolution of the Mixed General Routing Problem. This problem, in which the service activity occurs both at some of the nodes and at some of the arcs and edges of a mixed graph, contains a large number of important arc and node routing problems as special cases. Here, a large family of facet-defining inequalities, the Honeycomb inequalities, is described. Furthermore, a cutting-plane algorithm for this problem that incorporates new separation procedures for the K-C, Regular Path-Bridge, and Honeycomb inequalities is presented. Branch and bound is invoked when the final solution of the cutting-plane procedure is fractional. …

Mathematical optimizationmedicine.medical_specialtyBranch and boundPolyhedral combinatoricsMixed graphHoneycomb (geometry)Mixed rural postman problemManagement Science and Operations ResearchPolyhedral combinatoricsComputer Science ApplicationsRural postman problemVehicle routing problemmedicineDestination-Sequenced Distance Vector routingRouting (electronic design automation)General routing problemMATEMATICA APLICADACutting-plane methodMathematics
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SU-E-T-530: Comparison of Analytical and Monte Carlo Calculations for Heterogeneity Corrections in LDR Prostate Brachytherapy

2013

Purpose: It is well‐known that tissue heterogeneities and calcifications have significant influence on low energy brachytherapy. The aim of this work is to study the application of a simplified analytic algorithm that could be compatible with commercial Treatment Planning System (TPS) based on TG‐43. The algorithm, based on the classic equivalent path length method, has been compared with Monte Carlo (MC) computations using Penelope2009. Methods: The analytical model scales the distance from the seed to the calculation point according to the electronic density of the medium relative to water. Then, the dose is calculated from TG‐43 consensus data (stored on a TPS) by scaling the radial dose…

Mathematical optimizationmedicine.medical_treatmentComputationBrachytherapyMonte Carlo methodGeneral MedicineFunction (mathematics)Imaging phantomPath lengthmedicineDosimetryApplied mathematicsProstate brachytherapyMathematicsMedical Physics
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Best Proximity Points for Some Classes of Proximal Contractions

2013

Given a self-mapping g: A → A and a non-self-mapping T: A → B, the aim of this work is to provide sufficient conditions for the existence of a unique point x ∈ A, called g-best proximity point, which satisfies d g x, T x = d A, B. In so doing, we provide a useful answer for the resolution of the nonlinear programming problem of globally minimizing the real valued function x → d g x, T x, thereby getting an optimal approximate solution to the equation T x = g x. An iterative algorithm is also presented to compute a solution of such problems. Our results generalize a result due to Rhoades (2001) and hence such results provide an extension of Banach's contraction principle to the case of non-s…

Mathematical optimizationmetric spacesArticle SubjectIterative methodApplied Mathematicslcsh:MathematicsWork (physics)proximal contractionbest proximity pointExtension (predicate logic)Resolution (logic)lcsh:QA1-939Nonlinear programmingReal-valued functionPoint (geometry)Settore MAT/03 - GeometriaContraction principleAnalysisMathematicsAbstract and Applied Analysis
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An advanced pavement management system based on a genetic algorithm for a motorway network

2013

Maintenance and improvement, through the rehabilitation, of the road infrastructure is a strategic and priority objective for road agencies, nevertheless the economic resources required are often inadequate. Within road management, the pavement management system (PMS) plays an essential role because of both the money needed and the performance that should be provided in terms of safety, ride quality and transport cost. The PMS is based on searching for a balanced solution between the lowest cost and the increased level of performance (i.e. pavement condition). In this paper a PMS multi-objective optimization method, was proposed, using a genetic algorithm (GA) to identify the best solution …

Mathematical optimizationmulti-objective optimizationComputer sciencepavement management systemGenetic algorithmPavement managementgenetic algorithmSettore ICAR/04 - Strade Ferrovie Ed Aeroportipavement management system genetic algorithm multi-objective optimization.Multi-objective optimization
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Solving dynamic memory allocation problems in embedded systems with parallel variable neighborhood search strategies

2015

International audience; Embedded systems have become an essential part of our lives, thanks to their evolution in the recent years, but the main drawback is their power consumption. This paper is focused on improving the memory allocation of embedded systems to reduce their power consumption. We propose a parallel variable neighborhood search algorithm for the dynamic memory allocation problem, and compare it with the state of the art. Computational results and statistical tests applied show that the proposed algorithm produces significantly better outcomes than the previous algorithm in shorter computing time.

Mathematical optimizationparallelismmetaheuristicsC dynamic memory allocationComputer sciencebusiness.industryApplied Mathematics[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]Static memory allocationPower consumptionEmbedded systemDiscrete Mathematics and Combinatoricsdynamic memory allocation problemembedded systemsState (computer science)businessMetaheuristicvariable neighborhood searchVariable neighborhood searchDrawbackStatistical hypothesis testing
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