Post-disaster multi-period road network repair: work scheduling and relief logistics optimization

We develop a multi-period bi-level programming model for the post-disaster road network repair work scheduling and relief logistics problem. A maximum relative satisfaction degree-based steady-state parallel genetic algorithm is designed to solve this model. In order to validate and test the effectiveness of the presented mathematical model and method, we use a network generator to create numerical examples with different scales and characteristics of road network. Our numerical analysis of the solutions shows that the proposed mathematical model and method can effectively assist the decision-makers to deal with the road network repair work scheduling and relief logistics optimization problem during the emergency response phase. This mathematical model and the approach being developed are applied to deal with the case of Wenchuan earthquake in China. The results show that the required CPU time is short enough such that it meets the time limitation in the emergency response phase, and the strategy of road network repair scheduling will allow repair of the damaged roads to be completed before the end of the planning time horizon by 14.93%. Furthermore, the strategy of relief logistics can provide an efficient relief allocation and transportation path.