author = "Kunigami, Guilherme and de Rezende, Pedro Jussieu and de Souza, 
                         Cid Carvalho and Yunes, Tallys Hoover",
          affiliation = "{Institute of Computing - UNICAMP} and {Institute of Computing - 
                         UNICAMP} and {Institute of Computing - UNICAMP} and {School of 
                         Business Administration - University of Miami}",
                title = "Determining an Optimal Visualization of Physically Realizable 
                         Symbol Maps",
            booktitle = "Proceedings...",
                 year = "2011",
               editor = "Lewiner, Thomas and Torres, Ricardo",
         organization = "Conference on Graphics, Patterns and Images, 24. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Visualization, cartography, computational geometry, integer linear 
             abstract = "Proportional symbol maps are an often used tool to aid 
                         cartographers and geo-science professionals to visualize data 
                         associated with events (e.g., earthquakes) or geo-positioned 
                         statistical data (e.g., population). At specific locations, 
                         symbols are placed and scaled so that their areas become 
                         proportional to the magnitudes of the events or data. Recent work 
                         approaches the problem of drawing these symbols algorithmically 
                         and defines metrics to be optimized to attain different kinds of 
                         drawings. We focus specifically on optimizing the visualization of 
                         physically realizable drawings of opaque disks by maximizing the 
                         sum of the visible borders of such disks. As this problem has been 
                         proven to be NP-hard, we provide an integer programming model for 
                         its solution along with decomposition techniques designed to 
                         decrease the size of input instances. We present computational 
                         experiments to assess the performance of our model as well as the 
                         effectiveness of our decomposition techniques. .",
  conference-location = "Macei{\'o}",
      conference-year = "Aug. 28 - 31, 2011",
             language = "en",
           targetfile = "86796-revised.pdf",
        urlaccessdate = "2020, Apr. 10"