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DC Field | Value | Language |
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dc.contributor.author | Anagnostou, A | - |
dc.contributor.author | Mintram, K | - |
dc.contributor.author | Taylor, SJE | - |
dc.coverage.spatial | Orlando, FL, USA | - |
dc.date.accessioned | 2025-01-29T15:45:27Z | - |
dc.date.available | 2025-01-29T15:45:27Z | - |
dc.date.issued | 2024-12-15 | - |
dc.identifier | ORCiD: Anastasia Anagnostou https://orcid.org/0000-0003-3397-8307 | - |
dc.identifier | ORCiD: Kate Mintram https://orcid.org/0000-0001-7180-9200 | - |
dc.identifier | ORCiD: Simon J.E. Taylor https://orcid.org/0000-0001-8252-0189 | - |
dc.identifier.citation | Anagnostou, A. Mintram, K. and Taylor, S.J.E. (2024) 'Supply Chain Resilience Optimization with Agent-Based Modeling (SCROAM): A Novel Hybrid Framework', 2024 Winter Simulation Conference (WSC), Orlando, FL, USA, 15-18 December, pp. 1209 - 1220. doi: 10.1109/WSC63780.2024.10838624. | en_US |
dc.identifier.isbn | 979-8-3315-3420-2 (ebk) | - |
dc.identifier.isbn | 979-8-3315-3421-9 (PoD) | - |
dc.identifier.issn | 0891-7736 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/30608 | - |
dc.description.abstract | Supply chains are vulnerable to an array of exogenous disruptions, including operational contingencies, natural disasters, terrorism, and political and geopolitical instability. In order to ensure resilience to these disruptions, supply chains can use mitigation strategies to minimize risk and maximize recovery. Modeling approaches can be utilized to determine the most appropriate mitigation strategies for a specific scenario; however, there is currently no recognized modeling framework which can be applied to all supply chain sectors. This paper describes the key disruption risks to supply chains; the resilience and optimization strategies and performance metrics employed by supply chains to mitigate these risks; and the applications of simulation modeling in supply chain management. We present a hybrid framework for using agent-based modeling, alongside early warning systems, many objective optimization and option awareness analysis, to manage exogenous risks for a non-specific supply chain. | en_US |
dc.format.extent | 1209 - 1220 | - |
dc.format.medium | Print-Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.rights | Copyright © 2024 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. See: https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelinesand-policies/post-publication-policies/ | - |
dc.rights.uri | https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelinesand-policies/post-publication-policies/ | - |
dc.source | 2024 Winter Simulation Conference (WSC) | - |
dc.source | 2024 Winter Simulation Conference (WSC) | - |
dc.subject | measurement | en_US |
dc.subject | supply chain management | en_US |
dc.subject | reviews | en_US |
dc.subject | prevention and mitigation | en_US |
dc.subject | terrorism | en_US |
dc.subject | supply chains | en_US |
dc.subject | alarm systems | en_US |
dc.subject | agent-based modeling | en_US |
dc.subject | optimization | en_US |
dc.subject | resilience | en_US |
dc.title | Supply Chain Resilience Optimization with Agent-Based Modeling (SCROAM): A Novel Hybrid Framework | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1109/WSC63780.2024.10838624 | - |
dc.relation.isPartOf | 2024 Winter Simulation Conference (WSC) | - |
pubs.finish-date | 2024-12-18 | - |
pubs.finish-date | 2024-12-18 | - |
pubs.publication-status | Published | - |
pubs.start-date | 2024-12-15 | - |
pubs.start-date | 2024-12-15 | - |
dc.identifier.eissn | 1558-4305 | - |
dcterms.dateAccepted | 2024-06-05 | - |
dc.rights.holder | Institute of Electrical and Electronics Engineers (IEEE) | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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FullText.pdf | Copyright © 2024 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. See: https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelinesand-policies/post-publication-policies/ | 1.31 MB | Adobe PDF | View/Open |
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