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A Parallel Genetic Algorithm for Clustering

Juha Kivijärvi, Joonas Lehtinen, Olli Nevalainen, A Parallel Genetic Algorithm for Clustering. TUCS Technical Reports 469, Turku Centre for Computer Science, 2002.

Abstract:

Parallelization of genetic algorithms (GAs) has received considerable attention
in recent years. The reason for this is the availability of suitable
computational resources and the need for solving harder problems in
reasonable time. We describe a new
parallel self-adaptive GA for solving the data clustering problem.
The algorithm utilizes island parallelization implemented
using genebank model, in which GA processes communicate with each
other only through the genebank process. This model allows one to
easily implement different migration topologies. Experiments show
that significant speedup can be reached by parallelization.
The effect of migration parameters is also studied and the development of
diversity is examined by several measures, some of which are new.

BibTeX entry:

@TECHREPORT{tKiLeNe02a,
  title = {A Parallel Genetic Algorithm for Clustering},
  author = {Kivijärvi, Juha and Lehtinen, Joonas and Nevalainen, Olli},
  number = {469},
  series = {TUCS Technical Reports},
  publisher = {Turku Centre for Computer Science},
  year = {2002},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI)

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