Enhancing Resilience of Interdependent Supply Chain Networks Against Delay-Time Cascading Failures With Recovery Resource Allocation
The growing interdependency between physical and cyber-supply networks makes it possible for disruptions to trigger cascading failures with a mix of structure failures and function failures. There are studies that proposed recovery strategies to improve the resilience of interdependent supply chain networks (ISCNs). However, they hardly ever consider the impacts of real-world failure delay time and recovery resource allocation on ISCN resilience. In this article, a delay-time mixed cascading failure (MCF) model is first proposed to describe the disruption propagation process in ISCNs. Then, three common boundary node-based recovery strategies are implemented in ISCNs subject to MCFs, and the recovery sequence of network nodes is optimized based on efficient resource allocation. Finally, through case studies on a real-life supply chain network and three artificial networks, the effectiveness of recovery strategies is evaluated by using two resilience-based metrics from the perspectives of network function and network structure. Moreover, the impacts of important tunable parameters on ISCN resilience are examined. The experimental results demonstrate that the proposed recovery strategies are superior to traditional recovery strategies. This study provides insights for future investment decision-making toward the enhancement of ISCN resilience with limited recovery resources.
Authors
- Peirui Qiao
- Jian Zhou (ORCID: https://orcid.org/0000-0003-3505-8117)
- Fengxia Zhang (ORCID: https://orcid.org/0000-0002-3063-1351)
- Yizhong Ma (ORCID: https://orcid.org/0009-0000-1589-8050)
Institutions
- Shandong University of Technology (CN)
- Nanjing University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Reliability
- Published
- 2024-11-11
- DOI
- https://doi.org/10.1109/tr.2024.3485247
- Citations
- 16
- Primary Topic
- Supply Chain Resilience and Risk Management
- Type
- article
- Field-Weighted Citation Impact
- 8.87
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Natural Science Foundation of Jiangsu Province