A decision-support tool for humanitarian distribution planners in the face of congestion at security check-points: a real-world case study

Abstract

In times of armed conflicts, various security check-points are placed by authorities to control the flow of merchandise into and within areas of conflicts. The flow of humanitarian trucks that is added to regular flow of commercial trucks together with the complex security procedures create congestion and long waiting times at the security check-points. This causes distribution costs to increase and shortages of relief-aid to the affected civil people to occur. The present study proposes a decision-support tool to assist planners and policymakers in building efficient plans for the distribution of relief-aid, taking into account congestion at security check-points. The proposed tool is built around a multi-item humanitarian distribution planning model which has as objective to minimise distribution and backordering costs subject to capacity constraints that reflect congestion effects using nonlinear clearing functions. Using the 2014 Gaza war as a case study, we illustrate the application of the proposed tool, model the underlying relief-aid humanitarian supply chain, estimate clearing functions at different security check-points, and conduct computational experiments. Our results show that taking congestion into account in distribution planning reduces average lead times, backorders, and distribution costs.