Search results for "heuristics"

showing 10 items of 191 documents

A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms

2014

The file attached to this record is the author's final peer reviewed version. The publisher's final version can be found by following the DOI link. The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the most successful operators. In this paper we extend the idea of the ensemble to multiple local search logics. In a memetic fashion, the search structure of an ensemble framework cooperatively/competitively optimizes the problem jointly with a pool of diverse local search algorithms. In this way, the algorithm progressively adapts…

Structure (mathematical logic)Theoretical computer sciencebusiness.industryComputer scienceMeta-heuristicsComputational intelligenceAdaptive algorithmsDifferential evolutionLocal search (optimization)OptimisationDifferential evolutionAdaptation (computer science)businessGlobal optimizationAlgorithmMetaheuristicEnsembleMemetic ComputingCurse of dimensionality
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Approximate Matching over Biological RDF Graphs

2012

In the last few years, the amount of biological interaction data discovered and stored in public databases (e.g., KEGG [2]) considerably increased. To this aim, RDF is a powerful representation for interactions (or pathways), since they can be modeled as directed graphs, often referred to as biological networks, where nodes represent cellular components and the (labeled or unlabeled) edges correspond to interactions among components. Often for a given organism some components are known to be linked by well studied interactions. Such groups of components are called modules and they can be represented by sub-graphs in the corresponding biological network model. At today, one of the most impor…

Theoretical computer scienceGraph databaseComputer scienceSearch engine indexingcomputer.file_formatcomputer.software_genreGraphBioinformatics network analysisApproximate matchingIsomorphismRDFKEGGHeuristicscomputerBiological networkNetwork analysis
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Heuristics for the Constrained Incremental Graph Drawing Problem

2019

Abstract Visualization of information is a relevant topic in Computer Science, where graphs have become a standard representation model, and graph drawing is now a well-established area. Within this context, edge crossing minimization is a widely studied problem given its importance in obtaining readable representations of graphs. In this paper, we focus on the so-called incremental graph drawing problem, in which we try to preserve the user’s mental map when obtaining successive drawings of the same graph. In particular, we minimize the number of edge crossings while satisfying some constraints required to preserve the position of vertices with respect to previous drawings. We propose heur…

Theoretical computer scienceOptimization problemCombinatorial optimizationInformation Systems and ManagementGeneral Computer ScienceComputer science0211 other engineering and technologiesHeuristicMetaheuristic02 engineering and technologyManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringGraph drawing0502 economics and business050210 logistics & transportation021103 operations researchHeuristic05 social sciencesComputer Science (all)SolverGraphVertex (geometry)VisualizationGraph drawingModeling and SimulationCombinatorial optimizationHeuristicsMathematicsofComputing_DISCRETEMATHEMATICS
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GPU-accelerated exhaustive search for third-order epistatic interactions in case–control studies

2015

This is a post-peer-review, pre-copyedit version of an article published in Journal of Computational Science. The final authenticated version is available online at: https://doi.org/10.1016/j.jocs.2015.04.001 [Abstract] Interest in discovering combinations of genetic markers from case–control studies, such as Genome Wide Association Studies (GWAS), that are strongly associated to diseases has increased in recent years. Detecting epistasis, i.e. interactions among k markers (k ≥ 2), is an important but time consuming operation since statistical computations have to be performed for each k-tuple of measured markers. Efficient exhaustive methods have been proposed for k = 2, but exhaustive thi…

Theoretical computer scienceSource codeGeneral Computer ScienceComputer scienceComputationmedia_common.quotation_subjectGPUBrute-force searchCUDAMutual informationcomputer.software_genreTheoretical Computer ScienceMutual informationCUDAModeling and SimulationEpistasisGWASNode (circuits)Data miningTupleHeuristicscomputermedia_commonJournal of Computational Science
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High Locality Representations for Automated Programming

2011

We study the locality of the genotype-phenotype mapping used in grammatical evolution (GE). GE is a variant of genetic programming that can evolve complete programs in an arbitrary language using a variable-length binary string. In contrast to standard GP, which applies search operators directly to phenotypes, GE uses an additional mapping and applies search operators to binary genotypes. Therefore, there is a large semantic gap between genotypes (binary strings) and phenotypes (programs or expressions). The case study shows that the mapping used in GE has low locality leading to low performance of standard mutation operators. The study at hand is an example of how basic design principles o…

Theoretical computer sciencebusiness.industryComputer scienceLocalityParse treeGenetic programmingcomputer.software_genreComputingMethodologies_ARTIFICIALINTELLIGENCEGrammatical evolutionLocal search (optimization)Edit distanceArtificial intelligenceHeuristicsbusinesscomputerNatural language processingSemantic gap
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Multiobjective GRASP with Path Relinking

2015

In this paper we review and propose different adaptations of the GRASP metaheuristic to solve multiobjective combinatorial optimization problems. In particular, we describe several alternatives to specialize the construction and improvement components of GRASP when two or more objectives are considered. GRASP has been successfully coupled with Path Relinking for single-objective optimization. Moreover, we propose different hybridizations of GRASP and Path Relinking for multiobjective optimization. We apply the proposed GRASP with Path Relinking variants to two combinatorial optimization problems, the biobjective orienteering problem and the biobjective path dissimilarity problem. We report …

TheoryofComputation_MISCELLANEOUSMathematical optimizationInformation Systems and ManagementGeneral Computer ScienceBiobjective optimizationGRASPCombinatorial optimization problemOrienteeringManagement Science and Operations ResearchMulti-objective optimizationIndustrial and Manufacturing EngineeringModeling and SimulationPath (graph theory)HeuristicsMetaheuristicMathematicsEuropean Journal of Operational Research
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Ensemble Feature Selection Based on the Contextual Merit

2001

Recent research has proved the benefits of using ensembles of classifiers for classification problems. Ensembles constructed by machine learning methods manipulating the training set are used to create diverse sets of accurate classifiers. Different feature selection techniques based on applying different heuristics for generating base classifiers can be adjusted to specific domain characteristics. In this paper we consider and experiment with the contextual feature merit measure as a feature selection heuristic. We use the diversity of an ensemble as evaluation function in our new algorithm with a refinement cycle. We have evaluated our algorithm on seven data sets from UCI. The experiment…

Training setComputer sciencebusiness.industryHeuristicPattern recognitionFeature selectionContext (language use)Machine learningcomputer.software_genreEvaluation functionComputingMethodologies_PATTERNRECOGNITIONEnsembles of classifiersFeature (computer vision)Artificial intelligenceHeuristicsbusinesscomputer
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Ensemble Feature Selection Based on Contextual Merit and Correlation Heuristics

2001

Recent research has proven the benefits of using ensembles of classifiers for classification problems. Ensembles of diverse and accurate base classifiers are constructed by machine learning methods manipulating the training sets. One way to manipulate the training set is to use feature selection heuristics generating the base classifiers. In this paper we examine two of them: correlation-based and contextual merit -based heuristics. Both rely on quite similar assumptions concerning heterogeneous classification problems. Experiments are considered on several data sets from UCI Repository. We construct fixed number of base classifiers over selected feature subsets and refine the ensemble iter…

Training setbusiness.industryComputer scienceFeature selectionPattern recognitionBase (topology)Machine learningcomputer.software_genreExpert systemRandom subspace methodComputingMethodologies_PATTERNRECOGNITIONEnsembles of classifiersFeature (machine learning)Artificial intelligencebusinessHeuristicscomputerCascading classifiers
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Communal Transportation: Challenges for Largescale Routing Heuristics

2007

In this report we review the central transportation logistics problems arising in the communal sector, using information gathered from several large communes in Finland and previous literature. Most of the communal transportation problems can be modelled as different variants of the vehicle routing problem. The basic features of the problems are described, modelled and analyzed, and the relevant previous research on the topics is reviewed. In addition, some possible new solution strategies are suggested.

Transport engineeringGeographyVehicle routing problemTransportation logisticsRouting (electronic design automation)HeuristicsSSRN Electronic Journal
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Improved heuristics for the regenerator location problem

2014

Telecommunication systems use optical signals to transmit information. The strength of a signal in an optical network deteriorates and loses power as it goes farther from the source, mainly due to attenuation. Therefore, to enable the signal to arrive its intended destination with good quality, it is necessary to regenerate the signal periodically using regenerators. These components are relatively expensive and therefore it is desirable to deploy as few of them as possible in the network. In the regenerator location problem (RLP), we are given an undirected graph, positive edge lengths, and a parameter specifying the maximum length that a signal can travel before its quality deteriorates a…

TraverseComputer scienceStrategy and ManagementReal-time computingGRASPManagement Science and Operations ResearchSignalComputer Science ApplicationsNetwork planning and designManagement of Technology and InnovationGraph (abstract data type)Node (circuits)Business and International ManagementHeuristicsAlgorithmMetaheuristicInternational Transactions in Operational Research
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