%0 Journal Article
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@archivingpolicy denypublisher denyfinaldraft12
%@nexthigherunit 8JMKD3MGPCW/3F3PAJE
%@nexthigherunit 8JMKD3MGPCW/449PGL8
%@secondarytype PRE PI
%@issn 1741-5977
%@issn 1741-5985
%D 2009
%4 dpi.inpe.br/plutao@80/2009/12.01.11.58
%T Application of a GEO + SA hybrid optimization algorithm to the solution of an inverse radiative transfer problem
%@usergroup administrator
%@usergroup banon
%@usergroup lattes
%@usergroup marciana
%V 17
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%F lattes: 8427569272485063 1 GalskiSousRamoSilv:2009:ApGEHy
%@versiontype publisher
%X In a former study (F.L. de Sousa, F.M. Ramos, F.J.C.P. Soeiro, and A.J. Silva Neto, Application of the generalized extremal optimization algorithm to an inverse radiative transfer problem, Inverse Probl. Sci. Eng. 15 (2007), pp. 699714), a new evolutionary optimization metaheuristic  the generalized extremal optimization (GEO) algorithm (F.L. de Sousa, F.M. Ramos, P.Paglione, and R.M. Girardi, A new stochastic algorithm for design optimization, AIAA J. 41 (2003), pp. 18081818)  was applied to the solution of an inverse problem of radiative properties estimation. A comparison with two other stochastic methods; simulated annealing (SA) and genetic algorithms (GA), was also performed, demonstrating GEOs competitiveness for that problem. In the present article, a recently developed hybrid version of GEO and SA (R.L. Galski, Development of improved, hybrid, parallel, and multiobjective versions of the generalized extremal optimization method and its application to the design of spatial systems, D.Sc. Thesis, Instituto Nacional de Pequisas Espaciais, Brazil, 2006, p. 279. INPE-14795-TDI/1238 (in Portuguese)) is applied to the same radiative transfer problem and the results obtained are compared with those from the previous study. The present approach was already foreseen (e.g. in F.L. de Sousa, F.M. Ramos, F.J.C.P. Soeiro, and A.J. Silva Neto, Application of the generalized extremal optimization algorithm to an inverse radiative transfer problem, Inverse Probl. Sci. Eng. 15 (2007), pp. 699714) as a technique that could significantly improve the performance of GEO for this problem. The idea is to make use of a scheduling for GEOs free parameter  in a similar way to the cooling rate of SA. The main objective of this approach is to combine the good exploration properties of GEO during the early stages of the search with the good convergence properties of SA at the end of the search.
%8 Apr.
%@area ETES
%@secondarykey INPE--PRE/
%@electronicmailaddress galski@ccs.inpe.br
%@documentstage not transferred
%K generalized extremal optimization algorithm, simulated annealing, genetic algorithms, inverse radiative transfer problem.
%@e-mailaddress galski@ccs.inpe.br
%@doi 10.1080/17415970802082690
%@group CRC-CRC-INPE-MCT-BR
%@group SCC-COF-INPE-MCT-BR
%@group DIR-DIR-INPE-MCT-BR
%N 3
%@dissemination WEBSCI; PORTALCAPES.
%P 321-334
%A Galski, Roberto Luiz,
%A de Sousa, Fabiano Luis,
%A Ramos, Fernando Manuel,
%A Silva Neto, Antonio J.,
%B Inverse Problems in Science and Engineering
%2 dpi.inpe.br/plutao@80/2009/12.01.11.58.11