Modelling and analysis of risk and reliability for a contingency logistics supply chain

Abstract

Contingency logistic supply chain design and performance are very important for rare events such as natural disasters, terrorist attacks, and other emergency conditions. Although there is ample work on the evaluation of supply chain systems in terms of their profitability and efficiency, there is little work on the effectiveness of the response time of the supply chain, as well as quantitative measures for the robustness of the design and the reliability of the supply chain. Depending on the contingency, the perceived risk may be different for different situations. The level of risk aversion is dependent on the decision maker and the uncertainties associated with the supply and demand for the contingency. In this study the risk associated with shortages due to the uncertainties in supply and demand in the supply chain are modelled using distortion. In addition, a numerical analysis is performed and the sensitivity of the parameters in a contingency logistic supply chain is analysed. Methods to improve the effectiveness of the contingency operation are examined by efficiently allocating available resources, supplies, and time, as well as modelling the decision maker's perception associated with the failure of a particular node. An array of optimization models are formulated and discussed. Each of these models enables a decision maker to examine a variety of trade-offs in a contingency logistics supply chain. For example, one model examines the acquisition of mitigation strategies and the reallocation of resources while taking into consideration the decision maker's risk aversion. The main contribution of this paper is the establishment of an analysis framework for modelling and analysing the risk and reliability of contingency logistic supply chains.