[en] We consider a common industrial bottleneck: when to start an operation that takes a lot of time and can process many units in a single batch, with uncertainty on the arrival time of the units. A dynamic programming algorithm is developed for the deterministic case as a baseline. The performance of this algorithm is compared with simple rule-based methods to evaluate the trade-off between operational simplicity and decision optimality. The methods and results are validated both theoretically and computationally by using data from real industrial settings.
Research Center/Unit :
Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège
Disciplines :
Computer science
Author, co-author :
Hervers, Florent ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science
Derval, Guillaume ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science
Louveaux, Quentin ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science
Renard, Xavier
Language :
English
Title :
Stochastic batch scheduling in an industrial context
Publication date :
16 July 2026
Event name :
24th conference of the international federation of operational research societies
Event organizer :
International federation of operational research societies (IFORS)
Event place :
Vienna, Austria
Event date :
from 12 to 17 july 2026
Audience :
International
Name of the research project :
IA4APS
Funders :
SPW EER - Service Public de Wallonie. Economie, Emploi, Recherche
Funding text :
This thesis is funded by the Win4Doc program in collaboration with the company SmartYou
