Airport ground services optimization with gate assignment and reassignment

Abstract

This dissertation aims at solving the problem of gate assignment and the related problems on the airport ground surface. As the air traffic grows dramatically and the airport resources are insufficient to satisfy the growing air traffic growing, it is required to optimize the operation and utilization of current airport resources.

Firstly, a robust gate assignment problem is considered and solved by the state-of-the-art general MIP solving methods. Three factors having significant impact on gate assignment are considered: schedule robustness, facility and personnel cost during tows, and passenger satisfaction level. Initially, a quadratic model is formulated which is intractable. The model is then transformed to an equivalent MIP model and four algorithms are developed including Diving, Local Branching, and Relaxation Induced Neighborhood Search (RINS), which are popular algorithms for solving general MIP models, together with a new algorithm Variable Reduction Neighborhood Search (VRNS), which hybridizes the strengths of RINS and Diving. Extensive experiments are performed to compare the performance of the proposed algorithms.

Although the imbedded robustness consideration will alleviate the expected gate conflict, large disruptions occurring in airport operations will still affect the original schedule of flights’ gate assignment. For international hub airports, the impact on the connection of flights and passengers is obvious. Therefore, the second problem focused by this dissertation isa gate reassignment problem that focuses on transfer passengers’ satisfaction level. Decomposition methods are proposed to heuristically solve the model to meet real-time solution requirement. The computational results show the competitive performance of the proposed methods.

Capacity limitation of gate, taxiway and runway in an airport is often the major limiting factor of air traffic operation. The incomplete assignment or reassignment plan neglecting the surface condition may lead to severe airport surface congestion. In addition, the reassignment schedule for an aircraft may be impractical due to the constraints on taxiway or runway. Therefore, this dissertation proposes an integrated algorithm to solve problems of gate reassignment and taxiway routing simultaneously. A set partitioning model with side constraint is proposed in which each possible aircraft route in the gate and taxiway is regarded as a decision variable. In addition to traditional set partitioning constraints, two types of constraints are proposed to maintain a minimum separation distance between aircrafts in the taxiway and ramp area. The preliminary results show that the proposed integrated algorithm outperforms the sequential method.