The Hierarchical Fair Competition (HFC) Model for Parallel Evolutionary Algorithms

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

@InProceedings{hu:2002:thfcmfpea,
  author =       "Jianjun Hu and Erik D. Goodman",
  title =        "The Hierarchical Fair Competition (HFC) Model for
                 Parallel Evolutionary Algorithms",
  booktitle =    "Proceedings of the 2002 Congress on Evolutionary
                 Computation CEC2002",
  editor =       "David B. Fogel and Mohamed A. El-Sharkawi and 
                 Xin Yao and Garry Greenwood and Hitoshi Iba and Paul Marrow and 
                 Mark Shackleton",
  pages =        "49--54",
  year =         "2002",
  publisher =    "IEEE Press",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  organisation = "IEEE Neural Network Council (NNC), Institution of
                 Electrical Engineers (IEE), Evolutionary Programming
                 Society (EPS)",
  ISBN =         "0-7803-7278-6",
  URL =          "http://garage.cse.msu.edu/papers/GARAGe02-05-01.pdf",
  DOI =          "doi:10.1109/CEC.2002.1006208",
  month =        "12-17 " # may,
  notes =        "CEC 2002 - A joint meeting of the IEEE, the
                 Evolutionary Programming Society, and the IEE. Held in
                 connection with the World Congress on Computational
                 Intelligence (WCCI 2002)",
  keywords =     "genetic algorithms, genetic programming, HFC model,
                 biology, evolutionary computation, fitness-based
                 admission threshold, hierarchical fair competition
                 model, higher-fitness subpopulations, low-fitness
                 subpopulations, parallel evolutionary algorithms,
                 premature convergence, society, stratified competition,
                 biology, convergence, evolutionary computation,
                 parallel algorithms",
  abstract =     "The HFC model for evolutionary computation is inspired
                 by the stratified competition often seen in society and
                 biology. Subpopulations are stratified by fitness.
                 Individuals move from low-fitness subpopulations to
                 higher-fitness subpopulations if and only if they
                 exceed the fitness-based admission threshold of the
                 receiving subpopulation, but not of a higher one. HFC's
                 balanced exploration and exploitation, while avoiding
                 premature convergence, is shown on a genetic
                 programming example.",
}

Genetic Programming entries for Jianjun Hu Erik Goodman

Citations