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dc.contributor.authorUrfalıoğlu, Onayen_US
dc.contributor.authorÇetin, A. Enisen_US
dc.contributor.authorKuruoğlu, E. E.en_US
dc.coverage.spatialAtlanta, GA, USA
dc.date.accessioned2016-02-08T11:35:00Z
dc.date.available2016-02-08T11:35:00Z
dc.date.issued2008-07en_US
dc.identifier.urihttp://hdl.handle.net/11693/26760
dc.descriptionDate of Conference: 12-16 July, 2008
dc.descriptionConference name: GECCO '08 Proceedings of the 10th annual conference on Genetic and evolutionary computation
dc.description.abstractA novel evolutionary global optimization approach based on adaptive covariance estimation is proposed. The proposed method samples from a multivariate Levy Skew Alpha-Stable distribution with the estimated covariance matrix to realize a random walk and so to generate new solution candidates in the mutation step. The proposed method is compared to the popular Differential Evolution method, which is one of the best general evolutionary global optimizers available. Experimental results indicate that the proposed approach yields a general improvement in the required number of function evaluations to solve global optimization problems. Especially, as shown in experiments, the underlying heavy tailed alpha-stable distribution enables a considerably more effective global search in more complex problems. Track: Evolution Strategies.en_US
dc.language.isoEnglishen_US
dc.source.titleGECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008en_US
dc.relation.isversionofhttps://doi.org/10.1145/1389095.1389200
dc.subjectAlpha-stable distributionen_US
dc.subjectEvolutionary optimizationen_US
dc.subjectGlobal optimizationen_US
dc.subjectHeavy tailed distributionen_US
dc.subjectLevy walken_US
dc.subjectCovariance matrixen_US
dc.subjectEvolutionary algorithmsen_US
dc.subjectFunction evaluationen_US
dc.subjectOptimizationen_US
dc.subjectAlpha-stable distributionsen_US
dc.subjectComplex problemsen_US
dc.subjectCovariance estimationsen_US
dc.subjectDifferential evolution methodsen_US
dc.subjectEvolution strategiesen_US
dc.subjectEvolutionary global optimizationsen_US
dc.subjectGlobal optimization problemsen_US
dc.subjectGlobal searchesen_US
dc.subjectNew solutionsen_US
dc.subjectOptimizersen_US
dc.subjectRandom walksen_US
dc.titleLevy walk evolution for global optimizationen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage537en_US
dc.citation.epage538en_US
dc.identifier.doi10.1145/1389095.1389200
dc.publisherACM


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