Stochastic dual dynamic integer programming for a multi-echelon lot-sizing problem with remanufacturing and lost sales

Abstract : We consider an uncapacitated multi-echelon lot-sizing problem within a remanufacturing system involving three production echelons: disassembly, refurbishing and reassembly. We seek to plan the production activities on this system over a multi-period horizon. We assume a stochastic environment, in which the input data of the optimization problem are subject to uncertainty. We consider a multi-stage stochastic integer programming approach relying on scenario trees to represent the uncertain information structure and propose a solution method based on an extension of the stochastic dual dynamic programming algorithm. Our results show that this approach can provide good quality solutions for large-size instances in a reasonable time and significantly outperforms the use of a stand-alone mathematical solver.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-02421713
Contributor : Céline Gicquel <>
Submitted on : Friday, December 20, 2019 - 4:18:05 PM
Last modification on : Wednesday, February 12, 2020 - 10:50:22 PM

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Franco Quezada, Céline Gicquel, Safia Kedad-Sidhoum. Stochastic dual dynamic integer programming for a multi-echelon lot-sizing problem with remanufacturing and lost sales. IEEE International Conference on Control, Decision and Information Technologies CODIT 2019, Apr 2019, Paris, France. pp.1254-1259, ⟨10.1109/CoDIT.2019.8820709⟩. ⟨hal-02421713⟩

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