Stochastic dual dynamic integer programming for a multi-echelon lot-sizing problem with remanufacturing and lost sales - Laboratoire Interdisciplinaire des Sciences du Numérique Access content directly
Conference Papers Year : 2019

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

Franco Quezada

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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Dates and versions

hal-02421713 , version 1 (20-12-2019)

Identifiers

Cite

Franco Quezada, Céline Gicquel, Safia Kedad-Sidhoum. Stochastic dual dynamic integer programming for a multi-echelon lot-sizing problem with remanufacturing and lost sales. CODIT 2019- 6th IEEE International Conference on Control, Decision and Information Technologies, Apr 2019, Paris, France. pp.1254-1259, ⟨10.1109/CoDIT.2019.8820709⟩. ⟨hal-02421713⟩
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