A stochastic dual dynamic integer programming for the uncapacitated lot-sizing problem with uncertain demand and costs

Franco Quezada, Céline Gicquel, Safia Kedad-Sidhoum

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019
EditorsJ. Benton, Nir Lipovetzky, Eva Onaindia, David E. Smith, Siddharth Srivastava
PublisherAssociation for the Advancement of Artificial Intelligence
Pages353-361
Number of pages9
ISBN (Electronic)9781577358077
DOIs
Publication statusPublished - 1 Jan 2019
Event29th International Conference on Automated Planning and Scheduling, ICAPS 2019 - Berkeley, United States
Duration: 11 Jul 201915 Jul 2019

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference29th International Conference on Automated Planning and Scheduling, ICAPS 2019
Country/TerritoryUnited States
CityBerkeley
Period11/07/1915/07/19

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