Reliable container supply chain under disruption.

In this study, we develop a reliable formulation based on a container network flow problem, along with the full implementation of an empty container management strategy in the context of an integer linear programming model. The proposed approach can play a key role in coping with disruption in the network and can offer a proactive measure for effective disruption management to maintain a stable level of reliability in supply capability. To formulate a reliable container network problem, we design the pattern of disruption, a rare and irregular uncertainty, based on binomial coefficients in the objective function. In this way, flow interruption due to disruption can be expressed in node- and arc-failures and can be properly managed. Furthermore, we provide a non-disruptive model based on a deterministic formulation derived from a bast-case scenario. Through numerical illustrations and sensitivity analyses, we conduct in-depth analyses on the impact of disruption in the container supply chain, and a benchmark model based on a bast-case scenario is used to determine disruption costs, for comparative study. In particular, the numerical experiments show that if both maritime and hinterland disruptions are not managed in advance, disruption costs derived from a benchmark model result in a significant surge according to increasing potential disruption risk. Throughout computational experiments, we also found that maritime disruption is more destructive to container supply capability than hinterland disruption is. In particular, critical findings show that when a certain level of threshold is violated, the proposed strategies are completely interrupted in a container supply chain. Therefore, proactive measures to keep up a reliability of container supply in a high-risk region are highly recommended for management side.