Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/119241
DC FieldValueLanguage
dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorLiu, Yen_US
dc.creatorWang, Sen_US
dc.creatorZhen, Len_US
dc.date.accessioned2026-06-10T07:13:26Z-
dc.date.available2026-06-10T07:13:26Z-
dc.identifier.issn0925-5273en_US
dc.identifier.urihttp://hdl.handle.net/10397/119241-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.subjectCarbon emissionen_US
dc.subjectGreen supply chain managementen_US
dc.subjectInteger programmingen_US
dc.subjectOnboard carbon capture storageen_US
dc.titleStrategic optimization of onboard carbon capture and storage for maritime supply chain managementen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume290en_US
dc.identifier.doi10.1016/j.ijpe.2025.109808en_US
dcterms.abstractThe shipping industry is essential to global supply chain management, acting as a fundamental driver of international commerce and economic growth. However, its significant carbon emissions pose a serious threat to the environment, exacerbating climate change and necessitating immediate action to reduce its environmental impact. In this context, Onboard Carbon Capture and Storage (OCCS) has emerged as a critical solution, providing an effective measure to lower emissions and support the transition toward green supply chain in shipping industry. Considering the interdependent decisions of ports and shipping companies, our research focuses on selecting ports and timing for carbon processing systems to maximize ports revenue, identifying vessels on specific routes for OCCS installation, and determining optimal ports for offloading captured carbon to minimize processing costs. To address these problems, we develop an integer programming model to optimize the decisions of both ports and shipping companies. Furthermore, to validate the model’s effectiveness, we conduct extensive numerical experiments and perform sensitivity analyses to evaluate how parameters related to carbon processing prices and costs, influence optimal decisions. Finally, we provide valuable insights for future research on OCCS optimization and scheduling in the maritime industry.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationInternational journal of production economics, Dec. 2025, v. 290, 109808en_US
dcterms.isPartOfInternational journal of production economicsen_US
dcterms.issued2025-12-
dc.identifier.artn109808en_US
dc.description.validate202606 bcchen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera4492a-
dc.identifier.SubFormID52942-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis research was supported by the National Natural Science Foundation of China (Grant numbers 72371221, 72394360, 72394362, and 72361137001), the Project of Science and Technology Commission of Shanghai Municipality China (grant number 23JC1402200).en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2028-12-31en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2028-12-31
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