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Méthodes multi-objectifs pour l’ordonnancement de lignes réentrantes

Abstract : This article presents the scheduling of a reentrant maintenance line with parallel machine stages. In this study the system is composed of machines with their upstream buffer and are modeled by queuing system. The criteria are the maximization of the utilization rate of the bottleneck and the minimization of the mean cycle time of the products. We present the results obtained by a multi-objective ant colony algorithm with local search (MOACS-LS), which are compared with the results obtained by one of the most competitive genetic algorithm called Non-dominated Sorting Genetic Algorithm version 2 (NSGA2). This two metaheuristics are coupled with a discrete event simulation module. Our results are compared with an industrial solution.
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Submitted on : Tuesday, March 3, 2020 - 4:22:14 PM
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Frédéric Dugardin, Lionel Amodeo, Farouk Yalaoui. Méthodes multi-objectifs pour l’ordonnancement de lignes réentrantes. Journal of Decision Systems, Abingdon Oxfordshire UK: Routledge Taylor & Francis Group, 2012, 18 (2), pp.231-255. ⟨10.3166/jds.18.231-255⟩. ⟨hal-02497432⟩



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