Energy-aware blocking hybrid flow shop scheduling problem with sequence-depend setup times and machine speed levels

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dc.contributor.authorMissaoui, Ahmeden
dc.contributor.authorOzturk, Cemalettinen
dc.contributor.authorO'Sullivan, Barryen
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2025-04-23T09:28:45Z
dc.date.available2025-04-23T09:28:45Z
dc.date.issued2025en
dc.description.abstractThe industry sector has the second largest energy demand after electricity generation. Given the high trend of energy prices, scarcity of its supply due to political instability and dependency on fossil fuels for its production makes energy the primary challenge for the manufacturing sector to stay competitive. Therefore, in addition to novel equipment technologies that use less energy, energy-efficient scheduling has also been a priority for manufacturing companies. In this study, the Hybrid Flowshop Scheduling Problem with Blocking Constraints and Sequence-Depend Setup Times (BHFS-SDST) is investigated for the minimization of makespan and total energy consumption (TEC). First, a novel bi-objective Mixed Integer Linear Programming (MILP) model is formulated and solved through augmented epsilon constraints. Then, a novel multi-objective approach based on Iterated Greedy meta-heuristic is developed for larger instances. Efficiency and the scalability of the proposed approaches are tested with small, medium, and large instances. Computational experiments show the effectiveness of developed methods in solving the BHFS-SDST problem.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMissaoui, A., Ozturk, C. and O'Sullivan, B. (2025) ‘Energy-aware blocking hybrid flow shop scheduling problem with sequence-depend setup times and machine speed levels’, Procedia Computer Science, 253, pp. 1134–1143. https://doi.org/10.1016/j.procs.2025.01.175en
dc.identifier.doi10.1016/j.procs.2025.01.175en
dc.identifier.eissn1877-0509en
dc.identifier.endpage1143en
dc.identifier.journaltitleProcedia Computer Scienceen
dc.identifier.startpage1134en
dc.identifier.urihttps://hdl.handle.net/10468/17293
dc.identifier.volume253en
dc.language.isoenen
dc.publisherElsevier B.V.en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/Research Centres Programme::Phase 2/12/RC/2289_P2/IE/INSIGHT_Phase 2 /en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/National Challenge Fund::Digital for Resilience Challenge/22/NCF/DR/11264/IE/Deep Learning based Transferrable Supply Chain Stress Test/en
dc.rights© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 6th International Conference on Industry 4.0 and Smart Manufacturingen
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectHybrid flowshopen
dc.subjectBlocking constrainten
dc.subjectSequence-depend setup timesen
dc.subjectMakespanen
dc.subjectEnergy consumptionen
dc.subjectMixed Integer Linear Programmingen
dc.subjectIterated greedyen
dc.titleEnergy-aware blocking hybrid flow shop scheduling problem with sequence-depend setup times and machine speed levelsen
dc.typeArticle (peer-reviewed)en
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