Supply Chain; Network Design; Facility Location; Humanitarian Aid; Pre-Positioning; Demand; Uncertainty; Efficiency;
Increasingly, humanitarian organizations have opened regional warehouses and pre-positioned resources locally. Choosing appropriate locations is not easy and frequently based on opportunities rather than rational decisions. Dedicated decision-support systems could help humanitarian practitioners design their supply networks.Academic literature suggests the use of commercial sector models but rarely considers the constraints and specific context of humanitarian operations, such as obtaining accurate data, high uncertainties, limited budgets and increasing pressure on cost efficiency.The authors propose a tooled methodology to properly support humanitarian decision makers in the design of their supply chains. Their contribution is based on the definition of aggregate scenarios to reliably forecast demand using past disaster data and future trends. Demand for relief items based on these scenarios is then fed to a mixed-integer linear programming model in order to improve current supply networks.The specifications of this model have been defined in close collaboration with humanitarian workers. The model allows analysis of the impact of alternative sourcing strategies and service level requirements on operational efficiency. It provides clear and actionable recommendations for a given context, bridging the gap between academics and humanitarian logisticians.The methodology was developed to be useful to a broad range of humanitarian organizations, and a specific application to the supply chain design of the International Federation of Red Cross and Red Crescent Societies is discussed in detail.