Design of a reliable logistics network with hub disruption under uncertainty

In this study, we design a reliable logistics network based on a hub location problem, which is less sensitive to disruption and it performs efficiently when disruption occurs. A new mixed-integer programming model is proposed to minimize the total sum of the nominal and expected failure costs. This model considers complete and partial disruption at hubs. In addition, we propose a new hybrid meta-heuristic algorithm based on genetic and imperialist competitive algorithms. We compare the performance of the proposed al- gorithm with a new lower bound method in terms of the CPU time and solution quality. Furthermore, we conclude that a considerable improvement in the reliability of the net- work can be achieved with only a slight increase in the total cost. Finally, we demonstrate that the networks designed using our model are less conservative and more robust to dis- ruption compared with those designed based on other robustness measures