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A partial nested decomposition approach for remanufacturing planning under uncertainty

Franco Quezada 1 Céline Gicquel 2 Safia Kedad-Sidhoum 3 
2 ROCS - Réseaux & Optimisation Combinatoire et Stochastique
LISN - Laboratoire Interdisciplinaire des Sciences du Numérique, SDD - Science des Données
3 CEDRIC - OC - CEDRIC. Optimisation Combinatoire
CEDRIC - Centre d'études et de recherche en informatique et communications
Abstract : We seek to optimize the production planning of a three-echelon remanufacturing system under uncertain input data. We consider a multi-stage stochastic integer programming approach and use scenario trees to represent the uncertain information structure. We introduce a new dynamic programming formulation that relies on a partial nested decomposition of the scenario tree. We then propose a new extension of the recently published stochastic dual dynamic integer programming algorithm based on this partial decomposition. Our numerical results show that the proposed solution approach is able to provide near-optimal solutions for large-size instances with a reasonable computational effort.
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Submitted on : Tuesday, September 21, 2021 - 8:47:59 PM
Last modification on : Wednesday, September 28, 2022 - 5:52:20 AM
Long-term archiving on: : Wednesday, December 22, 2021 - 7:25:20 PM


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Franco Quezada, Céline Gicquel, Safia Kedad-Sidhoum. A partial nested decomposition approach for remanufacturing planning under uncertainty. Advances in Production Management Systems - APMS 2021, Sep 2021, Nantes, France. pp.663-672, ⟨10.1007/978-3-030-85902-2_71⟩. ⟨hal-03351043⟩



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