Abstract:
The unpredictable nature and global impact of natural and man-made disasters enforce governments of disaster-prone regions to provide practical response plans to minimize damage, ecological disruption and loss of human life. Humanitarian logistics management is one of the key issues that should be considered for an appropriate response, in particular, the planning of the transport of commodities required during response and the evacuation of injured people. This study proposes a multi-objective stochastic programming model for relief chain logistics planning that integrates location, inventory, and routing decisions considering logistics flow of both commodities and injured people. The model features five objectives: minimizing weighted sum of unserved demand and unserved injury, minimizing travel time for flow of commodities and injured people and minimizing total costs associated with flow of commodities. The first two objectives pursue fairness – expending the best effort to ensure delivery of relief commodities and evacuation of injured people. The other objectives pursue the efficiency goal. The proposed model is solved as a mixed-integer programming model applying the augmented ε-constraint method. A case study is presented to illustrate the potential applicability of this model for disaster planning. The findings demonstrate that the proposed model can benefit making decisions on facility location, resource allocation, and routing decisions in cases of disaster relief and evacuation efforts.
