Cluster-based evolutionary design of digital circuits using all improved multi-expression programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{1274013,
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author = "Fatima Zohra Hadjam and Claudio Moraga and
Mohamed Benmohamed",
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title = "Cluster-based evolutionary design of digital circuits
using all improved multi-expression programming",
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booktitle = "Late breaking paper at Genetic and Evolutionary
Computation Conference {(GECCO'2007)}",
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year = "2007",
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month = "7-11 " # jul,
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editor = "Peter A. N. Bosman",
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isbn13 = "978-1-59593-698-1",
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pages = "2475--2482",
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address = "London, United Kingdom",
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keywords = "genetic algorithms, genetic programming, improved
multi-expression programming, islands model",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2007/docs/p2475.pdf",
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URL = "http://ls1-www.cs.uni-dortmund.de/pdf/Veroeffentlichungen/GECCO-2007.pdf",
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DOI = "doi:10.1145/1274000.1274013",
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publisher = "ACM Press",
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publisher_address = "New York, NY, USA",
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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.",
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notes = "Distributed on CD-ROM at GECCO-2007 ACM Order No.
910071",
- }
Genetic Programming entries for
Fatima Zohra Hadjam
Claudio Moraga
Mohamed Benmohamed
Citations