TY - JOUR
T1 - Supply Chain Network Robustness Against Disruptions
T2 - Topological Analysis, Measurement, and Optimization
AU - Zhao, Kang
AU - Scheibe, Kevin
AU - Blackhurst, Jennifer
AU - Kumar, Akhil
N1 - Publisher Copyright:
© 1988-2012 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - This paper focuses on understanding the robustness of a supply network in the face of a disruption. We propose a decision support system for analyzing the robustness of supply chain networks against disruptions using topological analysis, performance measurement relevant to a supply chain context, and an optimization for increasing supply network performance. The topology of a supply chain network has considerable implications for its robustness in the presence of disruptions. The system allows decision makers to evaluate topologies of their supply chain networks in a variety of disruption scenarios, thereby proactively managing the supply chain network to understand vulnerabilities of the network before a disruption occurs. Our system calculates performance measurements for a supply chain network in the face of disruptions and provides both topological metrics (through network analysis) and operational metrics (through an optimization model). Through an example application, we evaluate the impact of random and targeted disruptions on the robustness of a supply chain network.
AB - This paper focuses on understanding the robustness of a supply network in the face of a disruption. We propose a decision support system for analyzing the robustness of supply chain networks against disruptions using topological analysis, performance measurement relevant to a supply chain context, and an optimization for increasing supply network performance. The topology of a supply chain network has considerable implications for its robustness in the presence of disruptions. The system allows decision makers to evaluate topologies of their supply chain networks in a variety of disruption scenarios, thereby proactively managing the supply chain network to understand vulnerabilities of the network before a disruption occurs. Our system calculates performance measurements for a supply chain network in the face of disruptions and provides both topological metrics (through network analysis) and operational metrics (through an optimization model). Through an example application, we evaluate the impact of random and targeted disruptions on the robustness of a supply chain network.
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U2 - 10.1109/TEM.2018.2808331
DO - 10.1109/TEM.2018.2808331
M3 - Article
AN - SCOPUS:85044785291
SN - 0018-9391
VL - 66
SP - 127
EP - 139
JO - IEEE Transactions on Engineering Management
JF - IEEE Transactions on Engineering Management
IS - 1
M1 - 8329409
ER -