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@InCollection{SambattiCampChiw:2019:PaAl,
               author = "Sambatti, Sabrina B. M. and Campos Velho, Haroldo Fraga de and 
                         Chiwiacowski, Leonardo D.",
                title = "Epidemic Genetic Algorithm for solving inverse problems: parallel 
                         algorithms",
            booktitle = "Integral methods in science and engineering",
            publisher = "Springer",
                 year = "2019",
               editor = "Constanda, Christian and Harris, Paul",
                pages = "381--394",
              address = "Brighton, UK",
             keywords = "Genetic algorithm, parallel computing, inverse problem.",
             abstract = "Parallel Genetic Algorithm (PGA) is employed to solve inverse 
                         problems. The PGA is codified considering the island model 
                         (individuals are free to migrate to any other processor, subjected 
                         to specific rules); and steppingstone model (migration is allowed 
                         only for closest processors). The parallel code is generated using 
                         calls to the message passing communication library MPI (Message 
                         Passing Interface). In the our GA approach, a new genetic 
                         operator, named epidemic, is applied. The technique is employed to 
                         solve an inverse heat conduction problem of determining the 
                         initial temperature from the transient noisy temperature profile 
                         at a given time. This ill-posed problem requires the use of a 
                         regularization technique.",
          affiliation = "{Clima Tempo} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {University of Caxias}",
                 isbn = "978-3-030-16077-7",
             language = "en",
           targetfile = "sambatti-epidemic.pdf",
        urlaccessdate = "04 dez. 2020"
}


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