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Métaheuristiques pour le flow-shop de permutation bi-objectif stochastique

Abstract : Although evolutionary algorithms are commonly used for solving multi-objective problems on the one hand and stochastic problems on the other hand, very few studies have investigated these two aspects simultaneously. For instance, scheduling problems are usually tackled in a single-objective deterministic form, whereas they are clearly multi-objective and they are subject to a wide range of uncertainty. In this paper, we present different approaches to solve stochastic multi-objective optimization problems and apply them to a bi-objective permutation flow-shop scheduling problem with random processing times.
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Contributor : Arnaud Liefooghe <>
Submitted on : Thursday, April 3, 2008 - 1:49:16 PM
Last modification on : Thursday, April 22, 2021 - 2:23:41 PM
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  • HAL Id : inria-00269981, version 1


Arnaud Liefooghe, Laetitia Jourdan, Matthieu Basseur, El-Ghazali Talbi. Métaheuristiques pour le flow-shop de permutation bi-objectif stochastique. Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2008, 22 (2), pp.183--208. ⟨inria-00269981⟩



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