Parallel strategies for stochastic evolution

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Abstract

The paper discusses the parallelization of Stochastic Evolution metaheuristic, identifying effective parallelization for a distributed parallel environment. Multiobjective VLSI cell placement is used as an optimization problem. A comprehensive set of parallelization approaches are tested and an effective strategy is identified in terms of two underlying factors: workload division and the effect of parallelization on metaheuristic's search intelligence. The strategies are compared with parallelization of another similar evolutionary metaheuristic called Simulated Evolution. The role of the two mentioned underlying factors is discussed in parallelization of stochastic evolution, the parallelized version of which has not been presented before.

Original languageEnglish
Title of host publicationProceedings of The 7th International Conference on Intelligent Systems Design and Applications, ISDA 2007
Pages813-818
Number of pages6
DOIs
StatePublished - 2007

Publication series

NameProceedings of The 7th International Conference on Intelligent Systems Design and Applications, ISDA 2007

ASJC Scopus subject areas

  • General Computer Science
  • Computer Science Applications
  • Control and Systems Engineering

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