@Article{GalskiSousRamoSilv:2009:ApGEHy,
               author = "Galski, Roberto Luiz and de Sousa, Fabiano Luis and Ramos, 
                         Fernando Manuel and Silva Neto, Antonio J.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Application of a GEO + SA hybrid optimization algorithm to the 
                         solution of an inverse radiative transfer problem",
              journal = "Inverse Problems in Science and Engineering",
                 year = "2009",
               volume = "17",
               number = "3",
                pages = "321--334",
                month = "Apr.",
             keywords = "generalized extremal optimization algorithm, simulated annealing, 
                         genetic algorithms, inverse radiative transfer problem.",
             abstract = "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.",
                  doi = "10.1080/17415970802082690",
                  url = "http://dx.doi.org/10.1080/17415970802082690",
                 issn = "1741-5977 and 1741-5985",
                label = "lattes: 8427569272485063 1 GalskiSousRamoSilv:2009:ApGEHy",
        urlaccessdate = "09 maio 2024"
}