2026-07-25T05:43:43Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:23867 2025-11-12T13:10:40Z ddc:004 open_access

Modeling and Explaining an Industrial Workforce Allocation and Scheduling Problem Bleukx, Ignace Boumazouza, Ryma Guns, Tias Laage, Nadine Poveda, Guillaume modeling scheduling fairness explanations feasibility restoration We present an industrial case on workforce allocation and scheduling in the aircraft manufacturing industry, where available teams need to be assigned to logistical operations. This application presents several challenges such as the scale of the problem, the need for fair workload distribution, and the need for methods for mitigating unforeseen disruptions due to technical malfunctions or incompatible weather conditions. We compare different Constraint Programming (CP) models for the allocation and scheduling problems, with extra focus on modeling the workload balancing component. Additionally, we investigate different techniques for explaining infeasibility of a disrupted schedule, such as conflict computation using Minimal Unsatisfiable Subsets (MUSes) and feasibility restoration using Minimal Correction Subsets (MCSes) or constraint relaxations. Our experimental results show that by using appropriate modeling techniques, the problem can be solved in reasonable time, thereby producing fair schedules. Additionally, we show how invalidated schedules can be explained and restored efficiently to help human operators in solving disruptions to the schedule. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ignace Bleukx and Ryma Boumazouza and Tias Guns and Nadine Laage and Guillaume Poveda 2025 Is Part Of LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.CP.2025.6 urn:nbn:de:0030-drops-238670 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.6 eng https://creativecommons.org/licenses/by/4.0/legalcode