Search results for "algorithm."

showing 10 items of 4617 documents

On the Bias of Syntactic Geometric Recombination in Genetic Programming and Grammatical Evolution

2015

For fixed-length binary representations as used in genetic algorithms, standard recombination operators (e.g.,~one-point crossover) are unbiased. Thus, the application of recombination only reshuffles the alleles and does not change the statistical properties in the population. Using a geometric view on recombination operators, most search operators for fixed-length strings are geometric, which means that the distances between offspring and their parents are less than, or equal to, the distance between their parents. In genetic programming (GP) and grammatical evolution (GE), the situation is different since the recombination operators are applied to variable-length structures. Thus, most r…

education.field_of_studyGrammatical evolutionBinary search treePopulationCrossoverBinary numberGenetic programmingeducationRandom walkAlgorithmRecombinationMathematicsProceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation
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Optimizing the Integration Area and Performance of VLIW Architectures by Hardware/Software Co-design

2021

The cost and the performance are major concerns that the designers of embedded processors shall take into account, especially for market considerations. In order to reduce the cost, embedded systems rely on simple hardware architectures like VLIW (Very Long Instruction Word) processors and they look for compiler support. This paper aims at developing a design space explorer of VLIW architectures from different perspectives like processing performance and integration area. A multi-objective Genetic Algorithm (GA) was used to find the optimum hardware configuration of an embedded system and the optimization rules applied by compiler on the benchmarks code. The first step consisted in represen…

education.field_of_studyInstructions per cycleMemory hierarchyComputer sciencePopulationEvolutionary algorithmOptimizing compilerParallel computingcomputer.software_genreVery long instruction wordGenetic algorithmCompilereducationcomputer
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An adaption mechanism for the error threshold of XCSF

2020

Learning Classifier System (LCS) is a class of rule-based learning algorithms, which combine reinforcement learning (RL) and genetic algorithm (GA) techniques to evolve a population of classifiers. The most prominent example is XCS, for which many variants have been proposed in the past, including XCSF for function approximation. Although XCSF is a promising candidate for supporting autonomy in computing systems, it still must undergo parameter optimization prior to deployment. However, in case the later deployment environment is unknown, a-priori parameter optimization is not possible, raising the need for XCSF to automatically determine suitable parameter values at run-time. One of the mo…

education.field_of_studyLearning classifier systemComputer sciencePopulation0102 computer and information sciences02 engineering and technologyFunction (mathematics)01 natural sciencesSet (abstract data type)Function approximation010201 computation theory & mathematicsApproximation errorGenetic algorithm0202 electrical engineering electronic engineering information engineeringReinforcement learning020201 artificial intelligence & image processingeducationAlgorithmProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
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Multi-modal search for multiobjective optimization: an application to optimal smart grids management

2012

This paper studies the possibility to use efficient multimodal optimizers for multi-objective optimization. In this paper, the application area considered for such new approach is the optimal dispatch of energy sources in smart microgrids. The problem indeed shows a non uniform Pareto front and requires efficient optimal search methods. The idea is to exploit the potential of agents in population-based heuristics to improve diversity in the Pareto front, where solutions show the same rank and are thus equally weighted. Since Pareto dominance is at the basis of the theory of multi-objective optimization, most algorithms show the non dominance ranking as quality indicator, with some problem i…

education.field_of_studyMathematical optimizationEngineeringbusiness.industryPopulationPareto principleEvolutionary algorithmmultimodal functions optimization optimal management distributed energy resources multi-objective evolutionary optimization smart gridsMulti-objective optimizationSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaRankingGenetic algorithmeducationEnergy sourcebusinessHeuristics
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A hybrid evolution strategy for the open vehicle routing problem

2010

This paper presents a hybrid evolution strategy (ES) for solving the open vehicle routing problem (OVRP), which is a well-known combinatorial optimization problem that addresses the service of a set of customers using a homogeneous fleet of non-depot returning capacitated vehicles. The objective is to minimize the fleet size and the distance traveled. The proposed solution method manipulates a population of @m individuals using a (@m+@l)-ES; at each generation, a new intermediate population of @l offspring is produced via mutation, using arcs extracted from parent individuals. The selection and combination of arcs is dictated by a vector of strategy parameters. A multi-parent recombination …

education.field_of_studyMathematical optimizationGeneral Computer Sciencebusiness.industryComputer scienceOffspringPopulationManagement Science and Operations ResearchTabu searchSearch algorithmModeling and SimulationVehicle routing problemCombinatorial optimizationLocal search (optimization)Guided Local SearchArtificial intelligencebusinesseducationEvolution strategyMetaheuristicComputers & Operations Research
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Scheduling a cellular manufacturing system with GA

2002

The flexible manufacturing cell scheduling problem is considered with a multi-objective approach, pursuing together makespan minimisation and the in process job wait minimisation. The formulation of the scheduling problem is discussed, analysing how to generate well suited sequences, like generalised permutation sequences, and the proper construction of a JIT timing of activities. An evolutionary sequencing algorithm based on both classic genetic operators and hybrid operators is then proposed. The hybrid operators have been introduced to construct highly fit initial population, to perform periodically a local search on the population and to maintain enough genetical diversity in the actual…

education.field_of_studyMathematical optimizationScheduleJob shop schedulingbusiness.industryComputer scienceCellular manufacturingPopulationScheduling (production processes)Work in processHybrid algorithmMinimisation (clinical trials)Scheduling (computing)Production controlGenetic algorithmLocal search (optimization)businesseducation
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A hybrid genetic algorithm with local search

2001

Abstract A hybrid genetic algorithm with internal local search was developed for optimisations involving continuous variables. The reproduction probabilities were enhanced using the fitness values obtained when a local method was applied to each individual in the population. These estimations are more realistic, since consider not the apparent but the hidden, latent quality of each individual. The information gathered in the local search was also used to build an auxiliary population recording the successfully enhanced individuals, which allowed to detect the convergence and self-adapt the search limits. The size of this auxiliary population was kept constant by a cluster analysis strategy.…

education.field_of_studyMathematical optimizationbusiness.industryProcess Chemistry and TechnologyPopulation-based incremental learningPopulationComputer Science ApplicationsAnalytical ChemistryConvergence (routing)Genetic algorithmMemetic algorithmLocal search (optimization)DeconvolutionConstant (mathematics)educationbusinessAlgorithmSpectroscopySoftwareMathematicsChemometrics and Intelligent Laboratory Systems
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The inheritance of organogenic response in melon

1996

Previous studies have demonstrated variation in organogenic competence among plants within a population ofCucumis melo. In order to determine if leaf explant response is under genetic control, we investigated the distribution of the shoot regeneration frequency in F1 and F2 generations from parents representing extreme values forin vitro organogenic response. Results suggest a genetic model with two genes, partial dominance, independent segregation and similar effects for both genes.

education.field_of_studyMelonPopulationInheritance (genetic algorithm)food and beveragesOrganogenesisHorticultureBiologyGenetic modelShootBotanyeducationGeneExplant culturePlant Cell, Tissue and Organ Culture
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Selection on life-history traits and genetic population divergence in rotifers

2009

A combination of founder effects and local adaptation – the Monopolization hypothesis – has been proposed to reconcile the strong population differentiation of zooplankton dwelling in ponds and lakes and their high dispersal abilities. The role genetic drift plays in genetic differentiation of zooplankton is well documented, but the impact of natural selection has received less attention. Here, we compare differentiation in neutral genetic markers (FST) and in quantitative traits (QST) in six natural populations of the rotifer Brachionus plicatilis to assess the importance of natural selection in explaining genetic differentiation of life-history traits. Five life-history traits were measur…

education.field_of_studyNatural selectionGenetic driftEvolutionary biologyPopulationAsexual reproductionBiologyeducationEcology Evolution Behavior and SystematicsSelection (genetic algorithm)Local adaptationLife history theorySexual reproductionJournal of Evolutionary Biology
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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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