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An Adaptive Algorithm for constrained optimization problems

Abstract : Several methods have been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems. The most widely used are those based on penalty function, thanks to their simplicity. In this paper, we propose a new adaptative penalty approach for solving constrained optimization problems, based on the amount of feasible individuals in the population. This method uses specific selection and recombination operators adapted to the penalisation strategy. We demonstrate the power of this approach on the eleven test cases presented in the litterature.
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Contributor : Marc Schoenauer Connect in order to contact the contributor
Submitted on : Monday, November 27, 2006 - 4:18:55 PM
Last modification on : Friday, December 17, 2021 - 1:28:02 PM
Long-term archiving on: : Saturday, April 3, 2010 - 10:25:00 PM


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  • HAL Id : inria-00001273, version 1



Sana Ben Hamida, Marc Schoenauer. An Adaptive Algorithm for constrained optimization problems. PPSN 2000, Sep 2000, Paris, France. ⟨inria-00001273⟩



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