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Computing the Set of Approximate Solutions of an MOP with Stochastic Search Algorithms

Abstract : In this work we develop a framework for the approximation of the entire set of $\epsilon$-efficient solutions of a multi-objective optimization problem with stochastic search algorithms. For this, we propose the set of interest, investigate its topology and state a convergence result for a generic stochastic search algorithm toward this set of interest. Finally, we present some numerical results indicating the practicability of the novel approach.
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https://hal.inria.fr/inria-00157741
Contributor : Oliver Schuetze <>
Submitted on : Tuesday, October 23, 2007 - 9:59:56 PM
Last modification on : Thursday, May 28, 2020 - 9:22:09 AM
Document(s) archivé(s) le : Tuesday, September 21, 2010 - 2:45:02 PM

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  • HAL Id : inria-00157741, version 2

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Oliver Schuetze, Carlos A. Coello Coello, El-Ghazali Talbi. Computing the Set of Approximate Solutions of an MOP with Stochastic Search Algorithms. 2007. ⟨inria-00157741v2⟩

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