A partial nested decomposition approach for remanufacturing planning under uncertainty

Franco Quezada (1) , Céline Gicquel (2) , Safia Kedad-Sidhoum (3)

1 RO - Recherche Opérationnelle
2 ROCS - Réseaux & Optimisation Combinatoire et Stochastique - LISN
3 CEDRIC - OC - CEDRIC. Optimisation Combinatoire

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.

Mots clés: Stochastic lot-sizing; Remanufacturing; Multistage stochastic integer programming; Stochastic dual dynamic programming

Domaines: Recherche opérationnelle [math.OC]

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-03351043v1⟩