On Parallel Evolutionary Algorithms on the Computational Grid

  • N. Melab
  • E-G. Talbi
  • S. Cahon
Part of the Studies in Computational Intelligence book series (SCI, volume 22)


In this chapter, we analyze the major traditional parallel models of evolutionary algorithms. The analysis is a contribution in parallel evolutionary computation as unlike previously published studies it is placed within the context of grid computing1. The objective is to visit again the parallel models in order to allow their adaptation to grids taking into account the characteristics of such execution environments in terms of volatility, heterogeneity, large scale and multi-administrative domain. The proposed study is a part of a methodological approach for the development of frameworks dedicated to the reusable design of parallel EAs transparently deployable on computational grids. We give an overview of such frameworks and present a case study related to ParadisEO-CMW which is a porting of ParadisEO onto Condor and MW allowing a transparent deployment of the parallel EAs on grids.


Pareto Front Computational Grid Parallel Model Island Model Parallel Evaluation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer 2006

Authors and Affiliations

  • N. Melab
    • 1
  • E-G. Talbi
    • 1
  • S. Cahon
    • 1
  1. 1.Laboratoire d’Informatique Fondamentale de Lille UMR CNRS 8022INRIA Futurs - DOLPHIN Project Cité scientifique - 59655France

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