Cluster-based evolutionary design of digital circuits using all improved multi-expression programming

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

@InProceedings{1274013,
  author =       "Fatima Zohra Hadjam and Claudio Moraga and 
                 Mohamed Benmohamed",
  title =        "Cluster-based evolutionary design of digital circuits
                 using all improved multi-expression programming",
  booktitle =    "Late breaking paper at Genetic and Evolutionary
                 Computation Conference {(GECCO'2007)}",
  year =         "2007",
  month =        "7-11 " # jul,
  editor =       "Peter A. N. Bosman",
  isbn13 =       "978-1-59593-698-1",
  pages =        "2475--2482",
  address =      "London, United Kingdom",
  keywords =     "genetic algorithms, genetic programming, improved
                 multi-expression programming, islands model",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2007/docs/p2475.pdf",
  URL =          "http://ls1-www.cs.uni-dortmund.de/pdf/Veroeffentlichungen/GECCO-2007.pdf",
  DOI =          "doi:10.1145/1274000.1274013",
  publisher =    "ACM Press",
  publisher_address = "New York, NY, USA",
  abstract =     "Evolutionary Electronics (EE) is a research area which
                 involves application of Evolutionary Computation in the
                 domain of electronics. EE algorithms are generally able
                 to find good solutions to rather small problems in a
                 reasonable amount of time, but the need for solving
                 more and more complex problems increases the time
                 required to find adequate solutions. This is due to the
                 large number of individuals to be evaluated and to the
                 large number of generations required until the
                 convergence process leads to the solution. As a
                 consequence, there have been multiple efforts to make
                 EE faster, and one of the most promising choices is to
                 use distributed implementations. In this paper, we
                 propose a cluster-based evolutionary design of digital
                 circuits using a distributed improved multi expression
                 programming method (DIMEP). DIMEP keeps, in parallel,
                 several sub-populations that are processed by Improved
                 Multi-Expression Programming algorithms, with each one
                 being independent from the others. A migration
                 mechanism produces a chromosome exchange between the
                 subpopulations using MPI (Message Passing Interface) on
                 a dedicated cluster of workstations (Lido Cluster,
                 Dortmund University). This paper presents the main
                 ideas and shows preliminary experimental results.",
  notes =        "Distributed on CD-ROM at GECCO-2007 ACM Order No.
                 910071",
}

Genetic Programming entries for Fatima Zohra Hadjam Claudio Moraga Mohamed Benmohamed

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