Supply Chain Network Robustness Against Disruptions: Topological Analysis, Measurement, and Optimization

Kang Zhao, Kevin Scheibe, Jennifer Blackhurst, Akhil Kumar

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number8329409
Pages (from-to)127-139
Number of pages13
JournalIEEE Transactions on Engineering Management
Volume66
Issue number1
DOIs
StatePublished - Feb 2019

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Electrical and Electronic Engineering

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