A developmental solution to (dynamic) capacitated arc routing problems using genetic programming

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

  author =       "Thomas Weise and Alexandre Devert and Ke Tang",
  title =        "A developmental solution to (dynamic) capacitated arc
                 routing problems using genetic programming",
  booktitle =    "GECCO '12: Proceedings of the fourteenth international
                 conference on Genetic and evolutionary computation
  year =         "2012",
  editor =       "Terry Soule and Anne Auger and Jason Moore and 
                 David Pelta and Christine Solnon and Mike Preuss and 
                 Alan Dorin and Yew-Soon Ong and Christian Blum and 
                 Dario Landa Silva and Frank Neumann and Tina Yu and 
                 Aniko Ekart and Will Browne and Tim Kovacs and 
                 Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and 
                 Giovanni Squillero and Nicolas Bredeche and 
                 Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and 
                 Martin Pelikan and Silja Meyer-Nienberg and 
                 Christian Igel and Greg Hornby and Rene Doursat and 
                 Steve Gustafson and Gustavo Olague and Shin Yoo and 
                 John Clark and Gabriela Ochoa and Gisele Pappa and 
                 Fernando Lobo and Daniel Tauritz and Jurgen Branke and 
                 Kalyanmoy Deb",
  isbn13 =       "978-1-4503-1177-9",
  pages =        "831--838",
  keywords =     "genetic algorithms, genetic programming",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Philadelphia, Pennsylvania, USA",
  DOI =          "doi:10.1145/2330163.2330278",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "A developmental, ontogenic approach to Capacitated Arc
                 Routing Problems (CARPs) is introduced. The genotypes
                 of this method are constructive heuristics specified as
                 trees of mathematical functions which are evolved with
                 Genetic Programming (GP). In a genotype-phenotype
                 mapping, they guide a virtual vehicle which starts at
                 the depot. The genotype is used to compute a heuristic
                 value for each edge with unsatisfied demands. Local
                 information such as the visiting costs from the current
                 position, the remaining load of the vehicle, and the
                 edge demands are available to the heuristic. The
                 virtual vehicle then serves the edge with the lowest
                 heuristic value and is located at its end. This process
                 is repeated until all requirements have been satisfied.
                 The resulting phenotypes are sets of tours which, in
                 turn, are sequences of edges. We show that our method
                 has three advantages: 1) The genotypes can be reused to
                 seed the population in new GP runs. 2) The size of the
                 genotypes is independent from the problem scale. 3) The
                 evolved heuristics even work well in modified or
                 dynamic scenarios and are robust in the presence of
  notes =        "Also known as \cite{2330278} GECCO-2012 A joint
                 meeting of the twenty first international conference on
                 genetic algorithms (ICGA-2012) and the seventeenth
                 annual genetic programming conference (GP-2012)",

Genetic Programming entries for Thomas Weise Alexandre Devert Ke Tang