Search results for "Optimization"

showing 10 items of 2824 documents

Memetic Compact Differential Evolution for Cartesian Robot Control

2010

This article deals with optimization problems to be solved in the absence of a full power computer device. The goal is to solve a complex optimization problem by using a control card related to portable devices, e.g. for the control of commercial robots. In order to handle this class of optimization problems, a novel Memetic Computing approach is presented. The proposed algorithm employs a Differential Evolution framework which instead of processing an actual population of candidate solutions, makes use of a statistical representation of the population which evolves over time. In addition, the framework uses a stochastic local search algorithm which attempts to enhance the performance of th…

education.field_of_studyOptimization problemComputer sciencebusiness.industryPopulationComputational intelligenceTheoretical Computer ScienceRobot controlArtificial IntelligenceControl systemDifferential evolutionCartesian coordinate robotAlgorithm designArtificial intelligencebusinesseducationIEEE Computational Intelligence Magazine
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Opinion dynamics and stubbornness through mean-field games

2013

This paper provides a mean field game theoretic interpretation of opinion dynamics and stubbornness. The model describes a crowd-seeking homogeneous population of agents, under the influence of one stubborn agent. The game takes on the form of two partial differential equations, the Hamilton-Jacobi-Bellman equation and the Kolmogorov-Fokker-Planck equation for the individual optimal response and the population evolution, respectively. For the game of interest, we establish a mean field equilibrium where all agents reach epsilon-consensus in a neighborhood of the stubborn agent's opinion.

education.field_of_studyPartial differential equationControl and OptimizationDifferential equationMulti-agent systemPopulationComputer Science::Social and Information NetworksControl and Systems Engineering; Modeling and Simulation; Control and OptimizationInterpretation (model theory)Computer Science::Multiagent SystemsStochastic partial differential equationMean field theoryComputer Science::Systems and ControlControl and Systems EngineeringModeling and Simulationopinion dynamicseducationMathematical economicsGame theoryMathematics
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A Population-Based Approach to the Resource-Constrained Project Scheduling Problem

2004

We present a population-based approach to the RCPSP. The procedure has two phases. The first phase handles the initial construction of a population of schedules and these are then evolved until high quality solutions are obtained. The evolution of the population is driven by the alternative application of an efficient improving procedure for locally improving the use of resources, and a mechanism for combining schedules that blends scatter search and path relinking characteristics. The objective of the second phase is to explore in depth those vicinities near the high quality schedules. Computational experiments on the standard j120 set, generated using ProGen, show that our algorithm produ…

education.field_of_studyScheduleMathematical optimizationComputer sciencemedia_common.quotation_subjectPopulationResource constrainedGeneral Decision SciencesManagement Science and Operations ResearchProject scheduling problemSet (abstract data type)Path (graph theory)Theory of computationQuality (business)Heuristicseducationmedia_commonAnnals of Operations Research
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Diversity Management in Memetic Algorithms

2012

In Evolutionary Computing, Swarm Intelligence, and more generally, populationbased algorithms diversity plays a crucial role in the success of the optimization. Diversity is a property of a group of individuals which indicates how much these individuals are alike. Clearly, a group composed of individuals similar to each other is said to have a low diversity whilst a group of individuals dissimilar to each other is said to have a high diversity. In computer science, in the context of population-based algorithms the concept of diversity is more specific: the diversity of a population is a measure of the number of different solutions present, see [239].

education.field_of_studyTheoretical computer scienceComputer sciencebusiness.industryPopulationContext (language use)Swarm intelligenceEvolutionary computationMemetic algorithmLocal search (optimization)educationbusinessPremature convergenceDiversity (business)
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A Primer on Memetic Algorithms

2012

Memetic Algorithms (MAs) are population-based metaheuristics composed of an evolutionary framework and a set of local search algorithms which are activated within the generation cycle of the external framework, see [376]. The earliest MA implementation has been given in [621] in the context of the Travelling Salesman Problem (TSP) while an early systematic definition has been presented in [615]. The concept of meme is borrowed from philosophy and is intended as the unit of cultural transmission. In other words, complex ideas can be decomposed into memes which propagate andmutate within a population.Culture, in this way, constantly undergoes evolution and tends towards progressive improvemen…

education.field_of_studyTheoretical computer scienceComputer sciencebusiness.industrySurvival of the fittestPopulationContext (language use)Travelling salesman problemMemetic algorithmLocal search (optimization)educationbusinessCultural transmission in animalsMetaheuristic
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Large Networks of Dynamic Agents: Consensus under Adversarial Disturbances

2012

This paper studies interactions among homogeneous social groups within the framework of large population games. Each group is represented by a network and the behavior described by a two-player repeated game. The contribution is three-fold. Beyond the idea of providing a novel two-level model with repeated games at a lower level and population games at a higher level, we also establish a mean field equilibrium and study state feedback best-response strategies as well as worst-case adversarial disturbances in that context.

education.field_of_studyTheoretical computer scienceSequential gameGame Theory; optimization; controlDistributed computingStochastic gamePopulationNormal-form gameComputingMilieux_PERSONALCOMPUTINGCombinatorial game theoryBayesian gameGame TheoryRepeated gameeducationGame theoryoptimizationcontrolMathematics
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3D inter-subject medical image registration by scatter search

2005

Image registration is a very active research area in computer vision, namely it is used to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images. From this matching, the registration transformation we are searching, can be inferred by means of numerical methods. In this paper, we propose a scatter search (SS) algorithm to solve the matching problem. SS is a hybrid metaheuristic with a good trade-off between search space diversification and intensification. On the one hand, diversity is basically introduced from a population-based approach where syst…

education.field_of_studybusiness.industryPopulationImage registrationImage processingPoint set registrationSearch algorithmLocal search (optimization)Computer visionArtificial intelligencebusinesseducationMetaheuristicImage retrievalMathematics
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Future wood demands and ecosystem services trade-offs: A policy analysis in Norway

2023

To mitigate climate change, several European countries have launched policies to promote the development of a renewable resource-based bioeconomy. These bioeconomy strategies plan to use renewable biological resources, which will increase timber and biomass demands and will potentially conflict with multiple other ecosystem services provided by forests. In addition, these forest ecosystem services (FES) are also influenced by other, different, policy strategies, causing a potential mismatch in proposed management solutions for achieving the different policy goals. We evaluated how Norwegian forests can meet the projected wood and biomass demands from the international market for achieving m…

ekosysteemit (ekologia)Economics and Econometricsekosysteemipalvelutmulti-objective optimizationmetsäpolitiikkaSociology and Political Sciencemetsänkäsittelyforest managementForestryforest policyManagement Monitoring Policy and Lawecosystem servicesmonitavoiteoptimointi
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Computational procedures for plastic shakedown design of structures

2004

The minimum volume design problem of elastic perfectly plastic finite element structures subjected to a combination of fixed and perfect cyclic loads is studied. The design problem is formulated in such a way that incremental collapse is certainly prevented. The search for the structural design with the required limit behaviour is effected following two different formulations, both developed on the grounds of a statical approach: the first one operates below the elastic shakedown limit and is able to provide a suboptimal design; the second one operates above the elastic shakedown limit and is able to provide the/an optimal design. The Kuhn–Tucker conditions of the two problems provide usefu…

elastic plastic behaviourOptimal designControl and OptimizationComputer sciencebusiness.industryStructural engineeringshakedown designComputer Graphics and Computer-Aided DesignFinite element methodComputer Science ApplicationsShakedownelastic shakedown limitControl and Systems EngineeringBree diagramLimit (mathematics)Engineering design processbusinessoptimizationSoftwareStructural and Multidisciplinary Optimization
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Multiobjective muffler shape optimization with hybrid acoustics modelling

2010

Shape optimization of a duct system with respect to sound transmission loss is considered. The objective of optimization is to maximize the sound transmission loss at multiple frequency ranges simultaneously by adjusting the shape of a reactive muffler component. The noise reduction problem is formulated as a multiobjective optimization problem. The sound attenuation for each considered frequency is determined by a hybrid method, which requires solving Helmholtz equation numerically by finite element method. The optimization is performed using non-dominated sorting genetic algorithm, NSGA-II, which is a multi-objective genetic algorithm. The hybrid numerical method is flexible with respect …

elementtimenetelmäaaltoputkishape optimizationgenetic algorithmwaveguideäärellisten elementtien menetelmämuodonoptimointigeneettinen algoritmi
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