Airline hub network optimization design under uncertain demand

In order to help airlines plan route network reasonably and reduce operation cost, from the perspective of airlines, airport capacity is regarded as a function of arrival and departure flights to draw airport capacity envelope curve. Based on airport capacity envelope curve, a two-stage mixed integer stochastic programming model with multi-allocation and non-strictness under stochastic demand is established. In the first stage, the hub location of the network is determined, and in the second stage, the transportation routes of each city pair and the flow ratios of different routes under different demand scenarios are determined. When demand scenario is a discrete variable, the model is transformed into a deterministic equivalent programming. Then taking China Eastern Airlines as an example, 13 airports are selected to validate the model, and the sensitivity analysis of transportation cost discount factor is carried out. The results show that the hub airports selected under different discount factors are different, the larger the discount, the more the hub selected, the lower the total network cost, and the hub selected under three discount factor scenarios is in good agreement with the actual situation; in each discount factor case, when the demand is different, the layout of the route network is different; by comparing the model results between certain and uncertain demand, it is concluded that the total cost of the network is lower when the demand is uncertain. Therefore, the proposed stochastic programming model under uncertain demand is closer to reality, which can help airlines plan hub-and-spoke network that is in line with the actual situation, and determine their capacity share in hub airports.