SDGP: A developmental approach for traveling salesman problems

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Ouyang:2013:CIPLS,
  author =       "Jin Ouyang and Thomas Weise and Alexandre Devert and 
                 Raymond Chiong",
  title =        "SDGP: A developmental approach for traveling salesman
                 problems",
  booktitle =    "IEEE Workshop on Computational Intelligence In
                 Production And Logistics Systems (CIPLS 2013)",
  year =         "2013",
  month =        apr,
  pages =        "78--85",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CIPLS.2013.6595203",
  abstract =     "This paper presents an Evolutionary Algorithm using a
                 new ontogenic approach, called Staged Developmental
                 Genetic Programming (SDGP), for solving symmetric
                 Travelling Salesman Problems (TSPs). In SDGP, a
                 genotype-phenotype mapping (gpm) is used to refine
                 candidate solutions to a TSP - these candidate
                 solutions are represented as permutations. The gpm
                 performs several development steps, in each of which
                 such a permutation x is incrementally modified. In each
                 iteration within a development step, the process can
                 choose to either apply one of seven different
                 modifications to a specific section of x or do nothing.
                 The choice is made by the genotypes g, which are
                 functions assigning real-valued ratings to the possible
                 modifications. Smaller ratings are better and the
                 best-rated modification is then applied, if its rating
                 is lower than a given threshold. The genotypes are
                 evolved using tree-based Genetic Programming.
                 Comprehensive numerical simulation experiments show
                 that our proposed algorithm scales well with the
                 problem size and delivers competitive results compared
                 to other state-of-the-art approaches in the TSP
                 literature.",
  notes =        "Also known as \cite{6595203}",
}

Genetic Programming entries for Jin Ouyang Thomas Weise Alexandre Devert Raymond Chiong

Citations