Genetic Programming for Guiding Branch and Bound Search

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{kostikas:2004:lbp,
  author =       "Konstantinos Kostikas and Charalambos Fragakis",
  title =        "Genetic Programming for Guiding Branch and Bound
                 Search",
  booktitle =    "Late Breaking Papers at the 2004 Genetic and
                 Evolutionary Computation Conference",
  year =         "2004",
  editor =       "Maarten Keijzer",
  address =      "Seattle, Washington, USA",
  month =        "26 " # jul,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2004/LBP045.pdf",
  abstract =     "We propose how Genetic Programming (GP) can be used
                 for developing, in real time, problem-specific
                 heuristics for Branch and Bound (B&B) search. A GP run,
                 embedded into the B&B process, exploits the
                 characteristics of the particular problem being solved,
                 evolving a problem-specific heuristic expression. The
                 evolved heuristic replaces the default one for the rest
                 of the B&B search. The application of our method to
                 node selection for B&B based Mixed Integer Programming
                 is illustrated by incorporating the GP node selection
                 heuristic generator into a B&B MIP solver. The hybrid
                 system compares well with the unmodified solver using
                 DFS, BFS, or even the advanced Best Projection
                 heuristic when confronted with hard MIP problems from
                 the MIPLIB3 benchmarking suite.",
  notes =        "Part of \cite{keijzer:2004:GECCO:lbp}",
}

Genetic Programming entries for Konstantinos Kostikas Charalambos Fragakis

Citations