Robust Optimization for Emergency Scheduling of Oil Products After Disaster

Being one of the most important strategic materials, oil products play an irreplaceable role in the supply of emergency resources and the normal operation of various transportation vehicles. Faced with unexpected disasters, it is urgent to allocate oil products to the stricken areas. By taking the shortest emergency scheduling time and the lowest cost as the objective functions, this paper develops a multi-objective mixed integer linear programming (MILP) model accounting for multiple supply sites, multiple disaster sites, multiple transportation modes, uncertain demand and effectiveness of scheduling paths. To obtain the optimal scheduling scheme, the augmented $\varepsilon $ -constraint method (AUGMECON) is combined with a robust optimization approach to solve the model. Finally, the model is applied to an emergency scheduling problem under the earthquake that occurred in Sichuan China in 2008. The results show that the model can not only effectively work out the emergency scheduling problem of oil products under demand uncertainty, but also ensure the robustness and optimality of the solution. Moreover, a comparison between single-objective and multi-objective models, as well as the analysis under different control parameters and disturbing parameters, are provided to validate the proposed model.