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dc.contributor.authorGajda-Zagórska, E.
dc.contributor.authorSchaefer, R.
dc.contributor.authorSmolka, M.
dc.contributor.authorPardo, D. 
dc.contributor.authorAlvarez-Aramberri, J. 
dc.date.accessioned2016-12-05T16:49:58Z
dc.date.available2016-12-05T16:49:58Z
dc.date.issued2016-09-01
dc.identifier.issn1877-7503
dc.identifier.urihttp://hdl.handle.net/20.500.11824/328
dc.description.abstractWe propose a new memetic strategy that can solve the multi-physics, complex inverse problems, formulated as the multi-objective optimization ones, in which objectives are misfits between the measured and simulated states of various governing processes. The multi-deme structure of the strategy allows for both, intensive, relatively cheap exploration with a moderate accuracy and more accurate search many regions of Pareto set in parallel. The special type of selection operator prefers the coherent alternative solutions, eliminating artifacts appearing in the particular processes. The additional accuracy increment is obtained by the parallel convex searches applied to the local scalarizations of the misfit vector. The strategy is dedicated for solving ill-conditioned problems, for which inverting the single physical process can lead to the ambiguous results. The skill of the selection in artifact elimination is shown on the benchmark problem, while the whole strategy was applied for identification of oil deposits, where the misfits are related to various frequencies of the magnetic and electric waves of the magnetotelluric measurementsen_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectInverse problemsen_US
dc.subjectMemetic algorithmsen_US
dc.subjectMulti-objective optimization methodsen_US
dc.titleA multi-objective memetic inverse solver reinforced by local optimization methodsen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doi10.1016/j.jocs.2016.06.007
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.jocs.2016.06.007en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/644202en_US
dc.relation.projectIDES/1PE/SEV-2013-0323en_US
dc.relation.projectIDES/1PE/MTM2013-40824-Pen_US
dc.relation.projectIDEUS/BERC/BERC.2014-2017en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersionen_US
dc.journal.titleJournal of Computational Scienceen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España