A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty

Franco Quezada; Céline Gicquel; Safia Kedad-Sidhoum

doi:10.1007/978-3-030-85902-2_71

A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty

Franco Quezada, Céline Gicquel, Safia Kedad-Sidhoum

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings
Editors	Alexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, David Romero
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	663-672
Number of pages	10
ISBN (Print)	9783030859015
DOIs	https://doi.org/10.1007/978-3-030-85902-2_71
Publication status	Published - 1 Jan 2021
Event	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021 - Nantes, France Duration: 5 Sept 2021 → 9 Sept 2021

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	631 IFIP
ISSN (Print)	1868-4238
ISSN (Electronic)	1868-422X

Conference

Conference	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021
Country/Territory	France
City	Nantes
Period	5/09/21 → 9/09/21

Keywords

Multistage stochastic integer programming
Stochastic dual dynamic programming
Stochastic lot-sizing with remanufacturing

Access to Document

10.1007/978-3-030-85902-2_71

Cite this

Quezada, F., Gicquel, C., & Kedad-Sidhoum, S. (2021). A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty. In A. Dolgui, A. Bernard, D. Lemoine, G. von Cieminski, & D. Romero (Eds.), Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings (pp. 663-672). (IFIP Advances in Information and Communication Technology; Vol. 631 IFIP). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-85902-2_71

Quezada, Franco ; Gicquel, Céline ; Kedad-Sidhoum, Safia. / A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty. Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. editor / Alexandre Dolgui ; Alain Bernard ; David Lemoine ; Gregor von Cieminski ; David Romero. Springer Science and Business Media Deutschland GmbH, 2021. pp. 663-672 (IFIP Advances in Information and Communication Technology).

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title = "A Partial Nested Decomposition 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 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.",

keywords = "Multistage stochastic integer programming, Stochastic dual dynamic programming, Stochastic lot-sizing with remanufacturing",

author = "Franco Quezada and C{\'e}line Gicquel and Safia Kedad-Sidhoum",

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doi = "10.1007/978-3-030-85902-2\_71",

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Quezada, F, Gicquel, C & Kedad-Sidhoum, S 2021, A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty. in A Dolgui, A Bernard, D Lemoine, G von Cieminski & D Romero (eds), Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. IFIP Advances in Information and Communication Technology, vol. 631 IFIP, Springer Science and Business Media Deutschland GmbH, pp. 663-672, IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2021, Nantes, France, 5/09/21. https://doi.org/10.1007/978-3-030-85902-2_71

A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty. / Quezada, Franco; Gicquel, Céline; Kedad-Sidhoum, Safia.
Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. ed. / Alexandre Dolgui; Alain Bernard; David Lemoine; Gregor von Cieminski; David Romero. Springer Science and Business Media Deutschland GmbH, 2021. p. 663-672 (IFIP Advances in Information and Communication Technology; Vol. 631 IFIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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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Quezada F, Gicquel C, Kedad-Sidhoum S. A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty. In Dolgui A, Bernard A, Lemoine D, von Cieminski G, Romero D, editors, Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems - IFIP WG 5.7 International Conference, APMS 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 663-672. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-030-85902-2_71

A Partial Nested Decomposition Approach for Remanufacturing Planning Under Uncertainty

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