Airline Fleet Robust Optimization Approach under Stochastic Demand with Route Network Effects

In order to solve the problem of network effects under uncertain passenger demand in route network, the itinerary-based optimization model for passenger-mix problem was incorporated into airline fleet planning problem. According to the optimization method for fleet capacity allocation, the number of aircrafts in each fleet type, the frequencies of different type of aircrafts flying on each leg, and the number of spilling passengers on each itinerary were regarded as decision variables. The limitations including the maximum passenger demand on each itinerary, available flying frequency on each flight leg, and available block time of each fleet type were considered as constraints. A robust optimization model for airline fleet planning under demand uncertainty was constructed by using the "quantitative share index" to calculate the passenger spilling recapture rate. After generating a discrete scenario set of passenger demand under the route network environment, the scenario aggregation algorithm was employed to solve the proposed model. Simulation results of an empirical example indicate that the fleet planning cost gained from this proposed model is reduced by 1 670 700 Yuan compared to the traditional model. The stochastic planning solution to fleet planning cost in 3 different scenarios decreases by 198 800 Yuan, 210 200 Yuan, and 175 500 Yuan, respectively, as opposed to the deterministic solution to the minimum stochastic expectation values.