Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/143033
Title: | A graph-based model to measure structural redundancy for supply chain resilience | Authors: | Tan, Wen Jun Zhang, Allan Nengsheng Cai, Wentong |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2019 | Source: | Tan, W. J., Zhang, A. N., & Cai, W. (2019). A graph-based model to measure structural redundancy for supply chain resilience. International Journal of Production Research, 57(20), 6385-6404. doi:10.1080/00207543.2019.1566666 | Journal: | International Journal of Production Research | Abstract: | Globalisation and lean initiatives increase the vulnerabilities of the supply chains (SC), where disruptions in any plant in a supply chain network (SCN) can propagate throughout the whole SCN. Redundancy is part of the SC re-engineering to improve supply chain resilience (SCRES). This paper presents a conceptual model of an SCN using graph theory, considering the relationships between plants and materials. Based on the model, the structural redundancy of the SCN is measured, which is used to assess SCRES. This assessment approach focuses on the resilience of the SCN against disruptions. Case studies are discussed to illustrate the applicability of this model and show that increasing structural redundancy of the SCN improves SCRES against disruptions. | URI: | https://hdl.handle.net/10356/143033 | ISSN: | 0020-7543 | DOI: | 10.1080/00207543.2019.1566666 | Schools: | School of Computer Science and Engineering | Research Centres: | Singapore Institute of Manufacturing Technology | Rights: | This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 17 Jan 2019, available online: http://www.tandfonline.com/10.1080/00207543.2019.1566666 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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A graph-based.pdf | 524.07 kB | Adobe PDF | ![]() View/Open |
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