@article{982,
  author = {Andre Bevilaqua, Laurence Rodrigues do Amaral, Marcos Wagner de Souza Ribeiro},
  title = {GASNV Environment: Building Virtual Sewer Networks Optimized by Genetic Algorithms},
  journal = {Journal of Networking Technology},
  year = {2012},
  volume = {3},
  number = {4},
  doi = {},
  url = {http://www.dline.info/jnt/fulltext/v3n4/2.pdf},
  abstract = {Less than two thirds of the world population have access to improved sanitation facilities. This number shows a great disparity between regions when looking at the global picture. The most alarming problem is observed in Southern Asia, followed by Eastern Asia and Sub-Saharan Africa. There is a wide variety of sanitation problems being faced in the world and one of the most important among them is the lack of piped sewer systems. A lot of attention was focused on the optimal design of storm sewer networks in the past decades. Storm water networks, specifically, can be considered an essential part of the infrastructure of any society. Every aspect involved in the construction and maintenance of these networks requires a huge amount of investment. In general, the lack of sanitation facilities occurs due to the high cost involved at the implantation. The present work proposes a computational evolutionary environment aiming to provide an optimal decision regarding the implantation of piped sewer systems. The method uses Genetic Algorithms and Information Visualization concepts, and has as a main goal presenting an alternative method that may be used to improve the sanitation statistics by covering a larger area with piped sewer systems, and most of all, reducing the costs and impact of the implantation.},
}