Search results for "Fitness function"

showing 10 items of 15 documents

A generalization of Kingman's model of selection and mutation and the Lenski experiment.

2017

Kingman’s model of selection and mutation studies the limit type value distribution in an asexual population of discrete generations and infinite size undergoing selection and mutation. This paper generalizes the model to analyze the long-term evolution of Escherichia. coli in Lenski experiment. Weak assumptions for fitness functions are proposed and the mutation mechanism is the same as in Kingman’s model. General macroscopic epistasis are designable through fitness functions. Convergence to the unique limit type distribution is obtained.

0301 basic medicineStatistics and ProbabilityGeneralizationPopulationBiology01 natural sciencesModels BiologicalGeneral Biochemistry Genetics and Molecular Biology010104 statistics & probability03 medical and health sciencesStatisticsEscherichia coliApplied mathematicsQuantitative Biology::Populations and EvolutionLimit (mathematics)0101 mathematicsSelection GeneticeducationSelection (genetic algorithm)education.field_of_studyFitness functionGeneral Immunology and MicrobiologyApplied MathematicsGeneral MedicineQuantitative Biology::GenomicsBiological Evolution030104 developmental biologyDistribution (mathematics)Modeling and SimulationMutation (genetic algorithm)MutationEpistasisGeneral Agricultural and Biological SciencesMathematical biosciences
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Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design.

2016

Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial accelera…

050210 logistics & transportationPolynomialMathematical optimizationFitness function05 social sciencesPerspective (graphical)Motion (geometry)020101 civil engineering02 engineering and technologyTransition curve0201 civil engineeringComputer Science ApplicationsGeometric designComplex geometryGenetic algorithmGenetic algorithms Horizontal alignment Polynomial curve Transition curve0502 economics and businessHorizontal alignment.Polynomial curveSettore ICAR/04 - Strade Ferrovie Ed AeroportiReversingParametric equationAlgorithmCivil and Structural EngineeringMathematics
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A comparative study of partitioning methods for crowd simulations

2010

The simulation of large crowds of autonomous agents with realistic behavior is still a challenge for several computer research communities. In order to handle large crowds, some scalable architectures have been proposed. Nevertheless, the effective use of distributed systems requires the use of partitioning methods that can properly distribute the workload generated by agents among the existing distributed resources. In this paper, we analyze the use of irregular shape regions (convex hulls) for solving the partitioning problem. We have compared a partitioning method based on convex hulls with two techniques that use rectangular regions. The performance evaluation results show that the conv…

Convex hullMathematical optimizationFitness functionHeuristicComputer scienceDistributed computingIrregular shapeAutonomous agentRegular polygonLoad balancing (computing)Partition (database)CrowdsScalabilityCrowd simulationSoftwareApplied Soft Computing
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Structural bias in population-based algorithms

2014

Abstract Challenging optimisation problems are abundant in all areas of science and industry. Since the 1950s, scientists have responded to this by developing ever-diversifying families of ‘black box’ optimisation algorithms. The latter are designed to be able to address any optimisation problem, requiring only that the quality of any candidate solution can be calculated via a ‘fitness function’ specific to the problem. For such algorithms to be successful, at least three properties are required: (i) an effective informed sampling strategy, that guides the generation of new candidates on the basis of the fitnesses and locations of previously visited candidates; (ii) mechanisms to ensure eff…

FOS: Computer and information sciencesQA75Mathematical optimizationInformation Systems and ManagementPopulation-based algorithmsFitness landscapemedia_common.quotation_subjectPopulationStructural biasEvolutionary computationPopulation-based algorithmEvolutionary computationTheoretical Computer ScienceArtificial IntelligenceBlack boxEconometricsQuality (business)OptimisationAlgorithmic designNeural and Evolutionary Computing (cs.NE)educationMathematicsmedia_commonta113education.field_of_studyFitness functionPopulation sizeComputer Science - Neural and Evolutionary ComputingComputer Science ApplicationsControl and Systems EngineeringAlgorithmSoftwarePopulation variance
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Hybrid Genetic Algorithms in Data Mining Applications

2009

Genetic algorithms (GAs) are a class of problem solving techniques which have been successfully applied to a wide variety of hard problems (Goldberg, 1989). In spite of conventional GAs are interesting approaches to several problems, in which they are able to obtain very good solutions, there exist cases in which the application of a conventional GA has shown poor results. Poor performance of GAs completely depends on the problem. In general, problems severely constrained or problems with difficult objective functions are hard to be optimized using GAs. Regarding the difficulty of a problem for a GA there is a well established theory. Traditionally, this has been studied for binary encoded …

Fitness functionComputer scienceHybrid genetic algorithmsSimulated annealingGenetic algorithmData miningcomputer.software_genrecomputerTabu searchFSA-Red Algorithm
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Three-dimensional rigid motion estimation using genetic algorithms from an image sequence in an active stereo vision system

2004

This paper proposes a method for estimating the three-dimensional (3D) rigid motion parameters from an image sequence of a moving object. The 3D surface measurement is achieved using an active stereovision system composed of a camera and a light projector, which illuminates the objects to be analyzed by a pyramid-shaped laser beam. By associating the laser rays with the spots in the two-dimensional image, the 3D points corresponding to these spots are reconstructed. Each image of the sequence provides a set of 3D points, which is modeled by a B-spline surface. Therefore, estimating the 3D motion between two images of the sequence boils down to matching two B-spline surfaces. We consider the…

Fitness functionMachine visionComputer sciencebusiness.industryImage processingSimilarity measureAtomic and Molecular Physics and OpticsComputer Science Applicationslaw.inventionProjectorMotion fieldlawMotion estimationStructure from motionComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessJournal of Electronic Imaging
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A genetic algorithm for image segmentation

2002

The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm.

Fitness functionSettore INF/01 - Informaticabusiness.industrySegmentation-based object categorizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationReal imageMinimum spanning tree-based segmentationComputer Science::Computer Vision and Pattern RecognitionGenetic algorithmComputer visionSegmentationArtificial intelligencebusinessGenetic algorithm Image SegmentationMathematics
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Research of a Cellular Automaton Simulating Logic Gates by Evolutionary Algorithms

2003

This paper presents a method of using genetic programming to seek new cellular automata that perform computational tasks. Two genetic algorithms are used : the first one discovers a rule supporting gliders and the second one modifies this rule in such a way that some components appear allowing it to simulate logic gates. The results show that the genetic programming is a promising tool for the search of cellular automata with specific behaviors, and thus can prove to be decisive for discovering new automata supporting universal computation.

Fitness functionTheoretical computer scienceComputer sciencebusiness.industryComputationEvolutionary algorithmGenetic programmingCellular automatonAutomatonMobile automatonGenetic algorithmGenetic representationArtificial intelligencebusinessAsynchronous cellular automaton
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The facility layout problem approached using a fuzzy model and a genetic search

2005

The problem of facility layout design is discussed, taking into account the uncertainty of production scenarios and the finite production capacity of the departments. The uncertain production demand is modelled by a fuzzy number, and constrained arithmetic operators are used in order to calculate the fuzzy material handling costs. By using a ranking criterion, the layout that represents the minimum fuzzy cost is selected. A flexible bay structure is adopted as a physical model of the system while an effective genetic algorithm is implemented to search for a near optimal solution in a fuzzy contest. Constraints on the aspect ratio of the departments are taken into account using a penalty fun…

Mathematical optimizationAdaptive neuro fuzzy inference systemFitness functionFuzzy setFuzzy logicDefuzzificationIndustrial and Manufacturing EngineeringFuzzy sets genetic algorithm layout optimization robustnessFuzzy transportationArtificial IntelligenceFuzzy set operationsFuzzy numberSoftwareMathematicsJournal of Intelligent Manufacturing
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Biased Modern Heuristics for the OCST Problem

2011

Biasing modern heuristics is an appropriate possibility in designing problem-specific and high-quality modern heuristics. If we have knowledge about a problem we can bias the design elements of modern heuristics, namely the representation and search operator, fitness function, the initial solution, or even the search strategy. This chapter presents a case study on how the performance of modern heuristics can be increased by biasing the design elements towards high-quality solutions. Results show that problem-specific and biased modern heuristics outperform standard variants and even for large problem instances high-quality solutions can be found.

Mathematical optimizationFitness functionOperator (computer programming)Computer scienceSimulated annealingGenetic algorithmDesign elements and principlesRepresentation (mathematics)HeuristicsSpan tree
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