<p>Pandemics, geopolitical strife, and regional tensions in recent years have intensified the disruption risks faced by global supply chains. To address the growing need for resilience evaluation, a quantitative indicator is proposed for measuring supply chain susceptibility to disruptions. A supply chain network is represented as a multistate resilience supply chain network (MRSCN), where nodes denote suppliers, assemblers, and markets, and arcs represent logistics connections. Due to shared resources, production and transportation capacities may be limited. System reliability is defined as the probability that the MRSCN successfully delivers goods to markets. In contrast to previous studies, an algorithm is proposed that considers uncertainties in both transportation and production capacities. A quantitative metric, based on system reliability, is computed to evaluate the impact of newly added suppliers during disruption scenarios. By comparing reliability before and after supplier integration, the contribution of new suppliers to overall supply chain resilience is quantified. The algorithm further enables the identification and analysis of supply chain vulnerabilities, offering valuable insights for decision-makers.</p>

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An algorithm for assessing a multistate resilience supply chain network in terms of system reliability

  • Kuan-Yu Lin,
  • Yi-Kuei Lin

摘要

Pandemics, geopolitical strife, and regional tensions in recent years have intensified the disruption risks faced by global supply chains. To address the growing need for resilience evaluation, a quantitative indicator is proposed for measuring supply chain susceptibility to disruptions. A supply chain network is represented as a multistate resilience supply chain network (MRSCN), where nodes denote suppliers, assemblers, and markets, and arcs represent logistics connections. Due to shared resources, production and transportation capacities may be limited. System reliability is defined as the probability that the MRSCN successfully delivers goods to markets. In contrast to previous studies, an algorithm is proposed that considers uncertainties in both transportation and production capacities. A quantitative metric, based on system reliability, is computed to evaluate the impact of newly added suppliers during disruption scenarios. By comparing reliability before and after supplier integration, the contribution of new suppliers to overall supply chain resilience is quantified. The algorithm further enables the identification and analysis of supply chain vulnerabilities, offering valuable insights for decision-makers.