In this study, we consider facility location decisions for a humanitarian relief chain responding to quick-onset disasters. In particular, we develop a model that determines the number and locations of distribution centres in a relief network and the amount of relief supplies to be stocked at each distribution centre to meet the needs of people affected by the disasters. Our model, which is a variant of the maximal covering location model, integrates facility location and inventory decisions, considers multiple item types, and captures budgetary constraints and capacity restrictions. We conduct computational experiments to illustrate how the proposed model works on a realistic problem. Results show the effects of pre- and post-disaster relief funding on relief system's performance, specifically on response time and the proportion of demand satisfied. Finally, we discuss the managerial implications of the proposed model.

The increasing complexity and magnitude of global emergency relief operations create a critical need for effective and efficient humanitarian supply chain management processes. The irregular demand patterns and unusual constraints inherent in large-scale emergencies present unique challenges to physical supply systems. Indeed, the logistical needs of non-governmental organisations frequently surpass the capabilities of current emergency response approaches. There is only a limited body of research in humanitarian supply chain management, particularly in the area of inventory control. In this research, this limitation is addressed by developing a stochastic inventory control model that determines optimal order quantities and reorder points for a long-term emergency relief response.

The current growth in consumption results in resource reduction, increasing waste production and, ultimately, environmental deterioration. Both government and consumer concerns regarding these issues have been driving reduction efforts in waste and natural resource-usage. These environmental issues, in addition to economic opportunities, result in the concept of product cycles that oppose the traditional ‘one-way’ economy. One approach is to create product recovery networks in which used products are collected, reprocessed and later redistributed to the customer. Product recovery networks differ from typical forward-only networks. Therefore, specific work considering their issues is necessary. In this work, we study a closed-loop supply chain in which manufacturers produce new products and remanufacture used products. The decisions to be made are: which warehouses and collection centres should be open, which warehouses should have sorting capabilities and how much material should be transported between each pair of sites. The multi-period integer programming model uses the present worth method to jointly analyse investment and operational costs. A sensitivity analysis of the model is performed, and conclusions are made regarding model behaviour and performance.