Improving supply system reliability against random disruptions: Strategic protection investment

Supply chains, as vital systems to the well-being of countries and economies, require systematic approaches to reduce their vulnerability. In this paper, we propose a non linear optimisation model to determine an effective distribution of protective resources among facilities in service and supply systems so as to reduce the probability of failure to which facilities are exposed in case of external disruptions. The failure probability of protected assets depends on the level of protection investments and the ultimate goal is to minimise the expected facility-customer transport or travel costs to provide goods and services. A linear version of the model is obtained by exploiting a specialised network flow structure. Furthermore, an efficient GRASP solution algorithm is developed to benchmark the linearised model and resolve numerical difficulties. The applicability of the proposed model is demonstrated using the Toronto hospital network. Protection measures within this context correspond to capacity expansion investments and reduce the likelihood that hospitals are unable to satisfy patient demand during periods of high hospitalisation (e.g. during a pandemic). Managerial insights on the protection resource distribution are discussed and a comparison between probabilistic and worst-case disruptions is provided.