Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/12680
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dc.contributor.authorÇakırgil, Seray-
dc.contributor.authorYücel, Eda-
dc.date.accessioned2025-09-10T17:26:49Z-
dc.date.available2025-09-10T17:26:49Z-
dc.date.issued2025-
dc.identifier.issn0360-8352-
dc.identifier.urihttps://doi.org/10.1016/j.cie.2025.111478-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/12680-
dc.description.abstractThis study addresses an integrated optimization problem in pharmaceutical blister packaging operations, combining three interdependent decision layers: packaging design, machinery and mold investment, and long-term production planning. These decisions are critical for balancing material efficiency, cost-effectiveness, and operational feasibility under time-varying demand. While existing literature typically treats these components in isolation, we propose a novel mixed-integer programming model that captures their interactions within a unified framework. Solving this problem exactly is computationally challenging for real-world instances; thus, we develop a tailored metaheuristic approach based on Adaptive Large Neighborhood Search (ALNS), enhanced with problem-specific heuristics and local search. Computational experiments on realistic data from a leading Turkish pharmaceutical company demonstrate the effectiveness of our approach in generating high-quality solutions across different planning horizons and demand scenarios. Additionally, our model supports sustainability goals by reducing raw material usage in packaging design, contributing to lower carbon emissions during production. © 2025 Elsevier B.V., All rights reserved.en_US
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofComputers & Industrial Engineeringen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdaptive Large Neighborhood Searchen_US
dc.subjectBlister Packagingen_US
dc.subjectHeuristicsen_US
dc.subjectMixed Integer Linear Programmingen_US
dc.subjectPharmaceutical Industryen_US
dc.subjectProduction Planningen_US
dc.subjectDrug Productsen_US
dc.subjectHeuristic Methodsen_US
dc.subjectHeuristic Programmingen_US
dc.subjectInteger Linear Programmingen_US
dc.subjectInteger Programmingen_US
dc.subjectInvestmentsen_US
dc.subjectMachine Designen_US
dc.subjectMixed-Integer Linear Programmingen_US
dc.subjectPackagingen_US
dc.subjectPackaging Materialsen_US
dc.subjectAdaptive Large Neighborhood Searchesen_US
dc.subjectBlister Packagingen_US
dc.subjectHeuristicen_US
dc.subjectInteger Linear Programmingen_US
dc.subjectIntegrated Optimizationen_US
dc.subjectMixed Integer Linearen_US
dc.subjectPackaging Designsen_US
dc.subjectPharmaceutical Industryen_US
dc.subjectProduction Planningen_US
dc.subjectSolid Formsen_US
dc.subjectProduction Controlen_US
dc.titleOptimizing Blister Packaging Design for Solid-Form Pharmaceuticalsen_US
dc.typeArticleen_US
dc.departmentTOBB University of Economics and Technologyen_US
dc.identifier.volume209en_US
dc.identifier.scopus2-s2.0-105014273931-
dc.identifier.doi10.1016/j.cie.2025.111478-
dc.authorscopusid57215499785-
dc.authorscopusid24773991000-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
dc.identifier.wosqualityQ1-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
crisitem.author.dept02.4. Department of Industrial Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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