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In the post-disaster response phase, an efficient relief distribution strategy plays a vital role in alleviating suffering in disaster-stricken areas, which sometimes becomes challenging in humanitarian logistics. Most governments pre-located the relief goods at the pre-determined warehouses against possible disasters. Those goods must be shipped to the relief distribution centers (RDCs) to be further distributed to the victims in impacted areas upon the disasters. Secondary disasters can occur due to the first disaster and can occur relatively close in time and location, resulting in more suffering and making the relief distribution activities more challenging. The needs of additional RDCs must be determined as well in response to the secondary disasters. A robust optimization model is proposed to hedge against uncertainties in RDCs’ capacity and relief demand. Its objective is to minimize the sum of transportation cost, additional RDC cost, and shortage of commodities. The computational results are given to demonstrate the effectiveness of the proposed model. The sensitivity analysis gives an insight to the decision-makers.

Robust Design of Relief Distribution Networks Considering Uncertainty