%0 Conference Proceedings
%T Optimization for Lot-Sizing Problems Under Uncertainty: A Data-Driven Perspective
%+ HEC Montréal (HEC Montréal)
%+ Systèmes Logistiques et de Production (LS2N - équipe SLP  )
%+ Groupe d’études et de recherche en analyse des décisions (GERAD)
%+ Département Automatique, Productique et Informatique (IMT Atlantique - DAPI)
%A Metzker, Paula
%A Thevenin, Simon
%A Adulyasak, Yossiri
%A Dolgui, Alexandre
%< avec comité de lecture
%@ 978-3-030-85901-5
%( IFIP Advances in Information and Communication Technology
%B IFIP International Conference on Advances in Production Management Systems (APMS)
%C Nantes, France
%Y Alexandre Dolgui
%Y Alain Bernard
%Y David Lemoine
%Y Gregor von Cieminski
%Y David Romero
%I Springer International Publishing
%3 Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems (Part II)
%V AICT-631
%N Part II
%P 703 - 709
%8 2021-09-05
%D 2021
%R 10.1007/978-3-030-85902-2_75
%K Data-driven optimization
%K Lot-sizing problem
%K Optimization under uncertainties
%Z Computer Science [cs]
%Z Mathematics [math]/Combinatorics [math.CO]Conference papers
%X In a manufacturing context, the lot-sizing problems (LSP) determine the quantity to produce over a planning horizon. Often, the parameters used in the LSP models are unknown when the decisions are made, and this uncertainty has a critical impact on the quality of the decisions. However, the large amount of data that can nowadays be collected from the shop floor allows inferring information on the LSP parameters and their variability. Therefore, a recent research trend is to properly account for the uncertainty in the LSP optimization models. This work presents a survey on data-driven optimization approaches for the LSPs. We also provide a comparison of some promising optimization methodologies in the context of data-driven modeling of LSPs.
%G English
%Z TC5
%Z WG 5,7
%2 https://hal.science/hal-03337325v2/document
%2 https://hal.science/hal-03337325v2/file/520755_1_En_75_Chapter.pdf
%L hal-03337325
%U https://hal.science/hal-03337325
%~ UNIV-NANTES
%~ INSTITUT-TELECOM
%~ CNRS
%~ EC-NANTES
%~ UNAM
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-APMS
%~ IFIP-WG5-7
%~ LS2N
%~ LS2N-SLP
%~ LS2N-SLP-IMTA
%~ IMTA_DAPI
%~ LS2N-IMTA
%~ IMT-ATLANTIQUE
%~ INSTITUTS-TELECOM
%~ LS2N-MODELIS-IMTA
%~ NANTES-UNIVERSITE
%~ UNIV-NANTES-AV2022
%~ NU-CENTRALE
%~ IFIP-AICT-631