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hal.structure.identifierParallel Cooperative Multi-criteria Optimization [DOLPHIN]
dc.contributor.authorTAVARES, Jorge
hal.structure.identifierAdvanced Learning Evolutionary Algorithms [ALEA]
dc.contributor.authorTANTAR, Alexandru-Adrian
dc.contributor.authorMELAB, Nouredine
hal.structure.identifierParallel Cooperative Multi-criteria Optimization [DOLPHIN]
hal.structure.identifierLaboratoire d'Informatique Fondamentale de Lille [LIFL]
dc.contributor.authorTALBI, El-Ghazali
dc.contributor.editorSpringer
dc.date.issued2008
dc.date.conference2008-09-13
dc.description.abstractEnEvolutionary approaches to protein-ligand docking typically use a real-value encoding and mutation operators based on Gaussian and Cauchy distributions. The choice of mutation is important for an efficient algorithm for this problem.We investigate the effect of mutation operators by locality analysis. High locality means that small variations in the genotype imply small variations in the phenotype. Results show that Gaussian-based operators have stronger locality than Cauchy-based ones, especially if an annealing scheme is used to control the variance.
dc.language.isoen
dc.publisherSpringer
dc.title.enThe influence of mutation on protein-ligand docking optimization: a locality analysis
dc.typeCommunication dans un congrès
dc.identifier.doi10.1007/978-3-540-87700-4_59
dc.subject.halInformatique [cs]/Autre [cs.OH]
bordeaux.page589-598
bordeaux.volume5199
bordeaux.countryDE
bordeaux.conference.cityDortmund
bordeaux.peerReviewedoui
hal.identifierhal-00690373
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2008-09-17
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00690373v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2008&rft.volume=5199&rft.spage=589-598&rft.epage=589-598&rft.au=TAVARES,%20Jorge&TANTAR,%20Alexandru-Adrian&MELAB,%20Nouredine&TALBI,%20El-Ghazali&rft.genre=unknown


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