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Reports (Research Report) Year : 2004

EEDA : A New Robust Estimation of Distribution Algorithms


In this report we address a subtle but important limitation found in the literature for Estimation of Distribution Algorithms (EDAs): symmetric initializations of the EDAs around the optimal solution. We focus our study on the performance of certain EDAs (EMNA-global and PBIL-C) that are asymmetrically initialized far from the optimum. We show and explain the failure of these EDAs under these conditions. These observations lead us to develop a new EDA based on an eigenspace analysis, which we denote by EEDA (Eigenspace EDA). We conclude by analyzing this new EDA and by showing its strengths when compared with EMNA-global and PBIL-C when the optimal solution is unknown.


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Dates and versions

inria-00070802 , version 1 (19-05-2006)


  • HAL Id : inria-00070802 , version 1


Michael Wagner, Anne Auger, Marc Schoenauer. EEDA : A New Robust Estimation of Distribution Algorithms. [Research Report] RR-5190, INRIA. 2004, pp.16. ⟨inria-00070802⟩
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