Robust Design of Relief Distribution Networks Considering Uncertainty

Abstract

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.

An integrated operations model for supply of relief items under path disruptions

“…Ahmadi et al [ 3 ] constructed a depot location and last mile distribution routing model in an earthquake stricken area with an objective of minimizing the cost for opening a local depot and the distribution cost. Nayeem and Lee [ 21 ] proposed a robust design for relief distribution networks considering the uncertainty after the disaster. They considered the establishment of additional relief distribution centres to meet the demand caused by secondary disasters.…”

“…Maghfiroh and Hanaoka [ 19 ] proposed a multi-modal relief distribution model for disaster response operations, utilizing reactive capabilities of the decision makers to select suitable modes after the disaster. Nayeem and Lee [ 21 ] also considered the uncertainty after the disaster and the possible disruption of roads. Abazari et al [ 1 ] considered uncertain parameters in humanitarian operations and formulated a mixed integer non-linear programming model, which was solved by GAMS software for small problem instances and Grasshopper Optimization Algorithm for large problems.…”

Multi-Objective Modeling of Relief Items Distribution Network Design Problem in Disaster Relief Logistics Considering Transportation System and CO2 Emission

“… In studies such as Aghajani et al [19], Boostani et al [4], Nayeem and Lee [47] and Cheng et al [46] there are different methods to deal with various types of uncertainty in existing literature of disaster relief logistics, but the approach that has not been done in any of these studies is the robust fuzzy multi-objective approach that utilized in this research for the first time to deal with uncertainty. In general, the current study is the first study that to propose a robust fuzzy model for relief items distribution network design problem considering environmental (CO 2 emission), social (deprivation cost) and economic impacts under reliability and uncertainty.…”