Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/114587
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Logistics and Maritime Studies | en_US |
dc.contributor | Department of Industrial and Systems Engineering | en_US |
dc.creator | Li, H | en_US |
dc.creator | Wu, Y | en_US |
dc.creator | Xin, B | en_US |
dc.creator | Xu, M | en_US |
dc.creator | Su, S | en_US |
dc.date.accessioned | 2025-08-12T09:09:55Z | - |
dc.date.available | 2025-08-12T09:09:55Z | - |
dc.identifier.citation | v. 198, 104107 | - |
dc.identifier.issn | 1366-5545 | en_US |
dc.identifier.other | v. 198, 104107 | - |
dc.identifier.uri | http://hdl.handle.net/10397/114587 | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier Ltd | en_US |
dc.subject | Carbon neutrality | en_US |
dc.subject | Healthcare operations management | en_US |
dc.subject | Multi-objective optimization | en_US |
dc.subject | Patient flow | en_US |
dc.subject | Ε-constraint method | en_US |
dc.title | Optimal operational and carbon neutrality strategies for private hospitals : a multi-objective approach considering patient flow | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 198 | en_US |
dc.identifier.doi | 10.1016/j.tre.2025.104107 | en_US |
dcterms.abstract | Hospitals are now the fifth-largest source of global greenhouse gas (GHG) emissions. Despite this significant impact, the critical goal of achieving carbon neutrality is often overlooked in optimization studies on healthcare operations management. To address this gap, this paper proposes a novel multi-objective decision-making framework for private hospitals that balances patient health, environmental impact, and economic performance. This study tackles the intricate challenge of multi-objective optimization that maximizes patient utility and hospital profit while simultaneously minimizing net carbon emissions. An exact algorithm based on the ε-constraint method is employed to optimize hospital operational decisions by discretizing patient utility and net carbon emission targets into linear constraints on the non-concave profit objective. This approach guarantees Pareto-optimal solutions, thus enabling hospital decision-makers to select their preferred options among the three criteria: patient utility, environmental sustainability, and hospital profitability, while exploring the resulting trade-offs. Additionally, this study discusses the impacts of hospital operational decision changes on these objectives, particularly under scenarios where patient flow increases waiting time due to limited hospital capacity. To validate the practical significance of the proposed multi-objective optimization model and evaluate the effectiveness of the proposed algorithm, two case studies and sensitivity analyses are conducted. The results demonstrate that this approach effectively supports hospital decision-makers in making informed decisions that balance patient utility, carbon neutrality, and hospital profitability objectives. | en_US |
dcterms.accessRights | embargoed access | en_US |
dcterms.bibliographicCitation | Transportation research. Part E, Logistics and transportation review, June 2025, v. 198, 104107 | en_US |
dcterms.isPartOf | Transportation research. Part E, Logistics and transportation review | en_US |
dcterms.issued | 2025-06 | - |
dc.identifier.eissn | 1878-5794 | en_US |
dc.identifier.artn | 104107 | en_US |
dc.description.validate | 202508 bcch | en_US |
dc.description.oa | Not applicable | en_US |
dc.identifier.FolderNumber | a3980 | - |
dc.identifier.SubFormID | 51865 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | The work was supported in part by the Hong Kong Research Grants Council under Grants 15508021 and 15511424, and the NSFC/RGC Joint Research Scheme under Grant No. 72261160393 & N_PolyU590/22. | en_US |
dc.description.pubStatus | Published | en_US |
dc.date.embargo | 2028-06-30 | en_US |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
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