Search results for " optimization"

showing 10 items of 2367 documents

Recursion at the crossroads of sequence modeling, random trees, stochastic algorithms and martingales

2013

This monograph synthesizes several studies spanning from dynamical systems in the statistical analysis of sequences, to analysis of algorithms in random trees and discrete stochastic processes. These works find applications in various fields ranging from biological sequences to linear regression models, branching processes, through functional statistics and estimates of risk indicators for insurances. All the established results use, in one way or another, the recursive property of the structure under study, by highlighting invariants such as martingales, which are at the heart of this monograph, as tools as well as objects of study.

modèles auto-régressifs[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]estimation and prediction errorstochastic gradient algorithmschaîne de Markov à mémoire variable[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]Digital search treesvariable length Markov chainstrong laws for discrete martingalessuffix trietemps d'occurrences de motifsoptimisation stochastique.dynamical systemtrie des suffixesstochastic optimization.erreur d'estimation et de prédictionArbres digitaux de rechercheauto-regressive modelssystème dynamiquelois fortes de martingales discrètesalgorithmes de gradient stochastiques[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]occurrences time
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Shape optimization in contact problems based on penalization of the state inequality

1986

The paper deals with the approximation of optimal shape of elastic bodies, uni­laterally supported by a rigid, frictionless foundation. Original state inequality, describing the behaviour of such a body is replaced by a family of penalized state problems. The relation between optimal shapes for the original state inequality and those for penalized state equations is established. peerReviewed

msc:49M30msc:73k40frictionless plane contact [keyword]minimization of the total potential energy [keyword]msc:74M15linear-elastic sheet [keyword]rigid foundation [keyword]msc:74P99contact boundary curve [keyword]family of penalized state problems [keyword]existence [keyword]msc:49J40convergence [keyword]nonlinear programming problem [keyword]msc:73T05shape optimization [keyword]box constraints [keyword]msc:74S05linear equality constraint [keyword]msc:74A55linear inequality constraints [keyword]
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An Hypervolume based constraint handling technique for multi-objective optimization problems

2011

Formulation of structural optimization problems usually leads to the individuation of one or more objective functions to be minimized under different constraints. Many multi-objective evolutionary algorithms are approached by a Pareto-compliant ranking method, where no a priori information on the problem is needed and the concept of non-dominated solutions is used. In this paper a constraint handling technique based on the concept of hypervolume indicator is presented. Initially proposed to compare different multi-objective algorithms hypervolume indicator is the only single set quality measure to reflects the dominance of solution’s sets. The constraint handling technique proposed use an e…

multi-objective optimization constraints hypervolumeSettore ICAR/08 - Scienza Delle Costruzioni
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A visualization technique for accessing solution pool in interactive methods of multiobjective optimization

2015

<pre>Interactive methods of <span>multiobjective</span> optimization repetitively derive <span>Pareto</span> optimal solutions based on decision maker's preference information and present the obtained solutions for his/her consideration. Some interactive methods save the obtained solutions into a solution pool and, at each iteration, allow the decision maker considering any of solutions obtained earlier. This feature contributes to the flexibility of exploring the <span>Pareto</span> optimal set and learning about the optimization problem. However, in the case of many objective functions, the accumulation of derived solutions makes accessing the sol…

multidimensional scalingMathematical optimizationOptimization problemComputer Networks and CommunicationsComputer sciencevisualisointiPareto front visualizationcomputer.software_genreMulti-objective optimizationSet (abstract data type)menetelmätMultidimensional scalingMultiobjective optimizationdimensionality reductionFlexibility (engineering)pareto-tehokkuusDimensionality reductionMultiobjective optimization ; interactive methods ; Pareto front visualization ; dimensionality reduction ; multidimensional scalinginteractive methodsNIMBUSmonitavoiteoptimointiComputer Science ApplicationsVisualizationComputational Theory and MathematicsFeature (computer vision)interaktiivisuusData miningcomputer
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Implementation of sparse forward mode automatic differentiation with application to electromagnetic shape optimization

2011

In this paper, we present the details of a simple lightweight implementation of the so-called sparse forward mode automatic differentiation (AD) in the C++programming language. Our implementation and the well-known ADOL-C tool (which utilizes taping and compression techniques) are used to compute Jacobian matrices of two nonlinear systems of equations from the MINPACK-2 test problem collection. Timings of the computations are presented and discussed. Moreover, we perform the shape sensitivity analysis of a time-harmonic Maxwell equation solver using our implementation and the tapeless mode of ADOL-C, which implements the dense forward mode AD. It is shown that the use of the sparse forward …

muotoherkkyysanalyysishape sensitivity analysismuodon optimointishape optimizationautomatic differentiationautomaattinen derivointi
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A New Simple Function for Combustion and Cyclic Variation Modeling in Supercharged Spark Ignition Engines

2022

Research in the field of Internal Combustion (IC) engines focuses on the drastic reduction of both pollutant and greenhouse gas emissions. A promising alternative to gasoline and diesel fuel is represented by the use of gaseous fuels, above all green hydrogen but also Natural Gas (NG). In previous works, the authors investigated the performance, efficiency, and emissions of a supercharged Spark Ignition (SI) engine fueled with mixtures of gasoline and natural gas; a detailed research involving the combustion process of this kind of fuel mixture has been previously performed and a lot of experimental data have been collected. Combustion modeling is a fundamental tool in the design and optimi…

natural gasControl and OptimizationSettore ING-IND/08 - Macchine A Fluidointernal combustion engine; combustion modeling; cyclic variation; natural gasRenewable Energy Sustainability and the EnvironmentEnergy Engineering and Power Technologycombustion modelingElectrical and Electronic EngineeringInternal combustion enginecyclic variationEngineering (miscellaneous)Energy (miscellaneous)Energies; Volume 15; Issue 10; Pages: 3796
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Energy efficient resource allocation in heterogeneous software defined network: A reverse combinatorial auction approach

2015

In this paper, resource allocation for energy effi- ciency in heterogeneous Software Defined Network (SDN) with multiple network service providers (NSPs) is studied. The considered problem is modeled as a reverse combinatorial auction game, which takes different quality of service (QoS) requirements into account. The heterogeneous network selection associated with power allocation problem is optimized by maximizing the energy efficiency of data transmission. By exploiting the properties of fractional programming, the resulting non-convex Winner Determination Problem (WDP) is transformed into an equivalent subtractive convex optimization problem. The proposed reverse combinatorial auction ga…

network service providersComputer Science::Computer Science and Game TheoryMathematical optimizationenergiatehokkuusComputer scienceDistributed computingQuality of serviceSoftware Defined NetworksAuction algorithmSDNCombinatorial auctionResource allocationSoftware-defined networkingHeterogeneous networkEfficient energy use2015 IEEE/CIC International Conference on Communications in China (ICCC)
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A Multi-Objective Design Approach for the c Chart Considering Taguchi Loss Function

2014

The present paper proposes a multi-objective design approach for the c chart, considering in the optimization process of the chart parameters both the statistical and the economic objectives. In particular, the minimization of the hourly total quality related costs is the considered objective to carry out the economic goal, whereas the statistical objective is reached by the minimization the out-of-control average run length of the chart. A mixed integer non-linear constrained mathematical model is formulated to solve the treated multi-objective optimization problem, whereas the Pareto optimal frontier is described by the «-constraint method. In order to show the employment of the proposed …

non-linear constrained mathematical programming ModelTaguchi loss functione-constraint methodstatistical process controlPareto optimal frontiermulti-objective optimization problemSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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CALIBRATION OF LÉVY PROCESSES USING OPTIMAL CONTROL OF KOLMOGOROV EQUATIONS WITH PERIODIC BOUNDARY CONDITIONS

2018

We present an optimal control approach to the problem of model calibration for L\'evy processes based on a non parametric estimation procedure. The calibration problem is of considerable interest in mathematical finance and beyond. Calibration of L\'evy processes is particularly challenging as the jump distribution is given by an arbitrary L\'evy measure, which form a infinite dimensional space. In this work, we follow an approach which is related to the maximum likelihood theory of sieves. The sampling of the L\'evy process is modelled as independent observations of the stochastic process at some terminal time $T$. We use a generic spline discretization of the L\'evy jump measure and selec…

non-parametric maximum likelihood methodOptimization problemDiscretizationL ́evy processesoptimal control of PIDE010103 numerical & computational mathematics01 natural sciences93E10 (primary) 49K20 60G51 62G05 (secondary)010104 statistics & probabilitysymbols.namesakeConjugate gradient methodIMEX numerical methodQA1-939Applied mathematics0101 mathematicsMathematics - Optimization and ControlMathematicsKolmogorov-Fokker-Planck equationoptimal control of PIDE Kolmogorov-Fokker-Planck equation L ́evy processes non-parametric maximum likelihood method IMEX numerical method.SolverOptimal controlSpline (mathematics)Lévy processesModeling and SimulationLagrange multipliersymbolsAkaike information criterionMathematicsAnalysisMathematical Modelling and Analysis
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Katsaus muodon optimoinnin menetelmiin

2017

Tutkielma esittelee muodon optimoinnin menetelmiä sekä niiden historiaa luoden katsauksen menetelmien kehittymiseen sekä niiden keskinäisiin suhteisiin. Tällaisia ovat esimerkiksi menetelmän matemaattisen teorian “kehittyneisyys” ja ratkaisemisen tehokkuus tai soveltuvuus. Tarkoituksena on muodostaa yleiskuva siitä, mitä menetelmiä muodon optimointiin on jo kehitetty, selvittää, miten ajankohtaisia eri menetelmät ovat, miten menetelmät vertautuvat toisiinsa ja selvittää, mihin eri menetelmät soveltuvat. Lukijan odotetaan selvittävän tarvittavat taustatiedot, sillä tutkielma ei juurikaan esittele muodon optimoinnin matematiikkaa. This thesis presents shape optimization methods, their history…

optimaalinen suunnittelumuodon optimointishape optimizationdesign optimizationtopologian optimointitopology optimization
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