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EEDA : A New Robust Estimation of Distribution Algorithms

Michael Wagner 1 Anne Auger 1 Marc Schoenauer 1 
1 TANC - Algorithmic number theory for cryptology
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], Inria Saclay - Ile de France
Abstract : 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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Reports (Research report)
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Submitted on : Friday, May 19, 2006 - 9:40:40 PM
Last modification on : Wednesday, October 26, 2022 - 8:16:02 AM
Long-term archiving on: : Sunday, April 4, 2010 - 9:56:39 PM


  • 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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