Multi-Stage Optimization Method for Dispatch of Ground-Service Vehicles at the Airports During Peak Flight Period

During the peak hours of flights, the demand for ground service is more concentrated. Plus, the limited number of available handing vehicles for dispatching at the airport, flights delay occurs, which have caused losses to the airport in many aspects. Aiming at this issue, a multi-stage optimization method for dispatch of ground-services vehicles is proposed, with a focus on considering the routing and time window constraints of shuttle buses and refueling vehicles. The flight punctuality rate and delay time are used as evaluation indexes to dispatch-optimization. A capacity-cost network G₁ with four types of nodes and five types of arcs is developed. By setting appropriate arc capacity and cost parameters, the planning model of the minimum cost flow is determined, and Lagrangian relaxation heuristic algorithm is used to solve the problem. Through continuous optimization, the initial value of the dual gap, the allowable error, and the maximum number of iterations are set, and the prediction results are output. The flight operation status during peak hour is deeply analyzed, and an integer linear programming model is proposed based on a time-space network, in which the total delay of unserved flights is optimized in the first stage. Combined with the minimum-maximum theorem, a delay model for a single flight is developed to minimize the loss. Finally, based on the real flight data, simulation experiments and the method validation are carried out combing with the apron layout. The results shown that: ① the maximum number of flights served on-time by refueling and shuttle vehicles are 30 and 131, respectively; ② the minimum total delay of flights to be served are 223 and 542 min, respectively; ③ the total flight delay decreased by 21.56%, significantly shortening the flight delay and improving the overall operational efficiency at the airport.