Back to Search Start Over

A Stochastic Dual Dynamic Integer Programming for the Uncapacitated Lot-Sizing Problem with Uncertain Demand and Costs

Authors :
Quezada, Franco
Gicquel, Céline
Kedad-Sidhoum, Safia
Recherche Opérationnelle (RO)
LIP6
Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
Laboratoire de Recherche en Informatique (LRI)
CentraleSupélec-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)
CEDRIC. Optimisation Combinatoire (CEDRIC - OC)
Centre d'études et de recherche en informatique et communications (CEDRIC)
Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)
Gicquel, Céline
Source :
Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling, 29th International Conference on Automated Planning and Scheduling ICAPS2019, 29th International Conference on Automated Planning and Scheduling ICAPS2019, Jul 2019, Berkeley, United States. pp.353-361
Publication Year :
2021
Publisher :
Association for the Advancement of Artificial Intelligence (AAAI), 2021.

Abstract

International audience; We study the uncapacitated lot-sizing problem with uncertain demand and costs. We consider a multi-stage decision process and rely on a scenario tree to represent the uncertainty. We propose to solve this stochastic combinatorial optimization problem thanks to a new extension of the stochastic dual dynamic integer programming algorithm. Our results show that this approach can provide good quality solutions in a reasonable time for large-size instances.

Details

ISSN :
23340843 and 23340835
Volume :
29
Database :
OpenAIRE
Journal :
Proceedings of the International Conference on Automated Planning and Scheduling
Accession number :
edsair.doi.dedup.....26f421f5b0b2067308892aa760b9d2e1
Full Text :
https://doi.org/10.1609/icaps.v29i1.3498