About: In this paper, we develop a framework to classify the Global supply chain risk management problems and present an approach for the solution of these problems. The risk management problems need to be handled at three levels strategic, operational and tactical. In addition, risk within the supply chain might manifest itself in the form of deviations, disruptions and disasters. To handle unforeseen events in the supply chain there are two obvious approaches: (1) to design chains with built in risk-tolerance and (2) to contain the damage once the undesirable event has occurred. Both of these approaches require a clear understanding of undesirable events that may take place in the supply chain and also the associated consequences and impacts from these events. We focus our efforts on mapping out the propagation of events in the supply chain due to supplier non-performance, and employ our insight to develop a mathematical programming based model for strategic level deviation and disruption management. The first model, a simple integer quadratic optimization model, adapted from the Markowitz model, determines optimal partner selection with the objective of minimizing both the operational cost and the variability of total operational cost. This model offers a possible approach to robust supply chain design. Key words: Supply Chain Risk Management; Risk Management; Supply Chain Planning; Supply Chain Design; Mean-Variance Optimization; Cause-Consequence Diagrams; Failure Analysis.   Goto Sponge  NotDistinct  Permalink

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  • In this paper, we develop a framework to classify the Global supply chain risk management problems and present an approach for the solution of these problems. The risk management problems need to be handled at three levels strategic, operational and tactical. In addition, risk within the supply chain might manifest itself in the form of deviations, disruptions and disasters. To handle unforeseen events in the supply chain there are two obvious approaches: (1) to design chains with built in risk-tolerance and (2) to contain the damage once the undesirable event has occurred. Both of these approaches require a clear understanding of undesirable events that may take place in the supply chain and also the associated consequences and impacts from these events. We focus our efforts on mapping out the propagation of events in the supply chain due to supplier non-performance, and employ our insight to develop a mathematical programming based model for strategic level deviation and disruption management. The first model, a simple integer quadratic optimization model, adapted from the Markowitz model, determines optimal partner selection with the objective of minimizing both the operational cost and the variability of total operational cost. This model offers a possible approach to robust supply chain design. Key words: Supply Chain Risk Management; Risk Management; Supply Chain Planning; Supply Chain Design; Mean-Variance Optimization; Cause-Consequence Diagrams; Failure Analysis.
Subject
  • Optimization algorithms and methods
  • Supply chain management
  • Portfolio theories
  • Expense
  • Operational risk
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