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Fuzzy-metaheuristic methods to solve a hybrid flow shop scheduling problem with pre-assignment

Abstract : This paper deals with a particular version of the hybrid flow shop scheduling problem inspired from a real application in the automotive industry. Specific constraints such as pre-assigned jobs, non-identical parallel machines and non-compatibility between certain jobs and machines are considered in order to minimise the total tardiness time. A mixed-integer programming model that incorporates these aspects is developed and solved using ILOG Cplex software. Thus, because of the computation time constraint, we propose approximate resolution methods based on genetic and particle swarm optimisation algorithms coupled or not with fuzzy logic control. The effectiveness of these methods is investigated via computational experiments based on theoretical and real case instances. The obtained results show that fuzzy logic control improves the performances of both genetic and particle swarm optimisation algorithms significantly.
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https://hal-utt.archives-ouvertes.fr/hal-02493704
Contributor : Daniel Gavrysiak <>
Submitted on : Friday, February 28, 2020 - 9:30:26 AM
Last modification on : Saturday, February 29, 2020 - 1:35:31 AM

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Naim Yalaoui, Yassine Ouazene, Farouk Yalaoui, Lionel Amodeo, Halim Mahdi. Fuzzy-metaheuristic methods to solve a hybrid flow shop scheduling problem with pre-assignment. International Journal of Production Research, Taylor & Francis, 2013, 51 (12), pp.3609-3624. ⟨10.1080/00207543.2012.754964⟩. ⟨hal-02493704⟩

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