2026-07-20T07:52:12Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:26679 2026-07-13T14:00:38Z ddc:004 open_access

Constraint Programming for Mixed-Model Assembly Line Scheduling with Complex Industrial Constraints Povéda, Guillaume Tejero, Javier Buil Sanchidrian, Tamara Borreguero modeling scheduling heuristics multi-objective The aeronautical industry transitioned in the 90s to takt-paced, product-specific assembly lines. The current trend of increased customization and demand variability is pushing for a transition to flexible mixed-model assembly lines. We address a mid-term planning problem for an airframe assembly plant, modeled as a Resource-Constrained Project Scheduling Problem (RCPSP) with complex industrial constraints. This formulation serves a dual purpose: facilitating high-level production planning and validating plant designs, particularly during ramp-up scenarios. We specifically tackle challenges involving calendar-based preemption, variable resource capacity, and resource blocking between task groups. We propose a Constraint Programming (CP) formulation that optimizes conflicting objectives, including Tardiness and Just-in-Time costs. To ensure scalability for large industrial instances, we introduce a sequential solving method based on topological decomposition. The proposed approach proves effective in handling complex scenarios, acting as a foundation for more realistic models. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Guillaume Povéda and Javier Buil Tejero and Tamara Borreguero Sanchidrian 2026 Is Part Of LIPIcs, Volume 379, 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.CP.2026.46 urn:nbn:de:0030-drops-266793 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2026.46 eng https://creativecommons.org/licenses/by/4.0/legalcode