@InProceedings{RodriguesFall:2013:InMeSi,
               author = "Rodrigues, Erica Patias and Faller, Daiane Gracieli",
                title = "Integra{\c{c}}{\~a}o de Meta-heur{\'{\i}}stica e Sistema de 
                         Informa{\c{c}}{\~a}o Geogr{\'a}fica para a 
                         otimiza{\c{c}}{\~a}o espacial multiobjetivo",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "7225--7232",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The tool choice for allocation modeling in land use is essential 
                         to optimizing processes and assists in decision making. Therefore, 
                         the objective of this study is applying genetic algorithms (GA) 
                         for land use optimization in a particular geographic region, using 
                         data generated by geographic information systems (GIS). The 
                         objective functions were considered to minimize the cost of land 
                         use reallocation and the minimization of the difference in land 
                         use aptitude defined by an expert. Two constraints were applied; 
                         the unit contiguity of the same land use type and existence of 
                         permanent protection areas. The algorithm was applied to 
                         simplified data from Goi{\^a}nia metropolitan region (an area of 
                         900 km2), considering three types of use: urban, rural and 
                         preservation areas. The GAs initial population was 100 
                         individuals, crossover and mutation rate of 80% and 5%, 
                         respectively, over 200 generations. The experience acquired from 
                         the study case described, we conclude that the GA can be very 
                         effective in optimizing spatial allocation problems. Future works 
                         may be performed in order to decrease the processing time (e.g., 
                         using parallel computing) and in relation to the restriction of 
                         minimum contiguous area (considering relevant laws).",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "1396",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GKU4",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GKU4",
           targetfile = "p1396.pdf",
                 type = "Mudan{\c{c}}a de Uso e Cobertura da Terra",
        urlaccessdate = "09 maio 2024"
}