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.

A Java Application for Optimization of Stock Allocation in Contingency Logistics Networks: Colonor

“…According to Miman and Pohl (2008), the definition of the failure probability for the base i (probability that the base i is mission incapable due to lack of enough materials to perform the mission) can be given through Eq.1. (Eq.1) can be derived by conditioning on S i (Assuming exponential supply and demand).…”

“…Once the demand is less than supply, the base is assumed to be capable to perform the assigned mission, hence it is reliable (Thomas, 2002;Thomas, 2004;Xiong et al, 2017;Zhang et al, 2018;Tubis et al, 2017;Wang et al, 2016;Zhang et al, 2016;Zhou et al, 2016;Benyoucef et al, 2013). Miman and Pohl (2008) extends Thomas' work considering stocks to be hold by the base before a contingency occurs. Here, the base is assumed to be reliable if the demand it requires is less than the amount of stocks it holds plus the amount supplied to the base.…”

“…Here, the base is assumed to be reliable if the demand it requires is less than the amount of stocks it holds plus the amount supplied to the base. They provide a stock allocation algorithm based on importance measures (Miman and Pohl, 2008;Miman and Pohl, 2012;Dağ and Miman, 2015).…”

Petri nets-based method for operational risk analysis in supply chains based on timeliness and recovery time

“…The growing interest in analyzing risks to the supply chain stems from the fact that adverse events not only affect a single link in the logistics network but that their effects may be felt by both direct contractors and their downstream partners. 5 The literature highlights three primary sources of supply chain disruptions 6 : (1) random operational events, such as equipment failure, system deficiencies, and crew strikes, (2) natural disasters, such as earthquakes, floods, and hurricanes; (3) targeted actions aimed at causing disruption, including terrorism and political instability. It should also be noted that these disruptions may occur in the activities of individual links operating in the supply chain, that is, a manufacturer of finished products, suppliers at various stages of the supply chain, and distributors acting as intermediaries for the consumer market.…”

“…1,2 For this reason, numerous publications on the recent challenges of supply chain management address the assessment and risk management issues that exist in the current integrated systems. Researchers focus on undesirable events that may threaten to reduce the logistics service level in the supply chain (see Miman and Pohl 3 ). Moreover, the second research direction is connected with assessing the vulnerability of individual links to disruptions that occur within the framework of cooperation between partners (see Neureuther and Kenyon 4 ).…”