An Indirect Approach to the Three-dimensional Multi-pipe Routing Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Marcus Furuholmen and Kyrre Glette and Mats Hovin and 
                 Jim Torressen",
  title =        "An Indirect Approach to the Three-dimensional
                 Multi-pipe Routing Problem",
  booktitle =    "Proceedings of the 13th European Conference on Genetic
                 Programming, EuroGP 2010",
  year =         "2010",
  editor =       "Anna Isabel Esparcia-Alcazar and Aniko Ekart and 
                 Sara Silva and Stephen Dignum and A. Sima Uyar",
  volume =       "6021",
  series =       "LNCS",
  pages =        "86--97",
  address =      "Istanbul",
  month =        "7-9 " # apr,
  organisation = "EvoStar",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-12147-0",
  DOI =          "doi:10.1007/978-3-642-12148-7_8",
  abstract =     "This paper explores an indirect approach to the
                 Three-dimensional Multi-pipe Routing problem. Variable
                 length pipelines are built by letting a virtual robot
                 called a turtle navigate through space, leaving pipe
                 segments along its route. The turtle senses its
                 environment and acts in accordance with commands
                 received from heuristics currently under evaluation.
                 The heuristics are evolved by a Gene Expression
                 Programming based Learning Classifier System. The
                 suggested approach is compared to earlier studies using
                 a direct encoding, where command lines were evolved
                 directly by genetic algorithms. Heuristics generating
                 higher quality pipelines are evolved by fewer
                 generations compared to the direct approach, however
                 the evaluation time is longer and the search space is
                 more complex. The best evolved heuristic is short and
                 simple, builds modular solutions, exhibits some degree
                 of generalization and demonstrates good scalability on
                 test cases similar to the training case.",
  notes =        "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010
                 held in conjunction with EvoCOP2010 EvoBIO2010 and

Genetic Programming entries for Marcus Furuholmen Kyrre Harald Glette Mats Erling Hovin Jim Torressen