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Journal Articles International Journal of Production Research Year : 2022

A stochastic dual dynamic integer programming based approach for remanufacturing planning under uncertainty

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 approximate 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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Dates and versions

hal-03781178 , version 1 (20-09-2022)

Licence

Attribution - NonCommercial - NoDerivatives - CC BY 4.0

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Franco Quezada, Céline Gicquel, Safia Kedad-Sidhoum. A stochastic dual dynamic integer programming based approach for remanufacturing planning under uncertainty. International Journal of Production Research, inPress, pp.1-21. ⟨10.1080/00207543.2022.2120924⟩. ⟨hal-03781178⟩
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