Abstract: In order to determine the specific locations of hubs and optimize the path design of origin-destination (OD) flows of airline network, an interval scenario set was defined and a new absolute interval robust optimization model was established, taking into account the uncertainty of design parameters OD flows and unit flow cost of the hub-and-spoke network.The model was solved by combination of the modified shortest path algorithm with artificial intelligence algorithms, and then verified in two numerical cases using the classic data for airline network design and the OD data of Chinese airline network, respectively. The results show that the optimal solutions obtained from the absolute interval robust optimization model have global optimality, and the deterministic robust optimization model is a special case of the proposed model under pessimistic rules when the values of the OD flows and cost of unit flow are determined; the correlation coefficient of the two groups of objective values obtained from pessimistic and optimistic rules is more than 0.99 in different scenarios. In the standard example under the pessimistic rule, the optimal objective value calculated from the proposed model, after normalized, is 784.47, which is 16.65% less than the optimal objective value of the deterministic optimization model and 29.07% less than the optimal objective value of the relative interval robust optimization model.