This repository contains the implementations of our papers studying Airport Ground Handling (AGH) problems:

• Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling

Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, Zhenghua Chen

• Neural Airport Ground Handling

Yaoxin Wu*, Jianan Zhou*, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang

Note: These works were done in 2021 and 2022, respectively. Based on our experiments, we recommend building upon the code of the second work for further research.

We propose a learning-based improvement framework to solve large-scale Airport Ground Handling (AGH) instances. Specifically, we leverage the Large Neighborhood Search (LNS) framework, which consists of a pair of destroy and repair operators, to decompose the global (intractable) optimization problem and re-optimize each sub-problem. The operation scheduling in AGH is formulated as a mixed integer linear programming (MILP) model. To mitigate the need of domain expertise, 1) our proposed framework directly operates on the decision variables of the MILP model; 2) we employ an off-the-shelf solver (e.g., CPLEX) as the repair operator to conduct re-optimization. Our method could efficiently solve large-scale AGH instances with hundreds of flights, while CPLEX would simply stuck, even when searching for a feasible solution.

We propose a learning-based construction framework to solve Airport Ground Handling (AGH) problems in an end-to-end manner. The studied problem is modeled as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints, including precedence, time windows, and capacity. It is much more complicated than the simple VRPs (e.g., TSP/CVRP) studied in the major ML conferences. The proposed method could also serve as a simple learning-based baseline for further research on complicated VRPs (e.g., CVRPTW).

./
├── Construction_based               # The implementation of TITS paper
├── Improvement_based                # The implementation of TKDE paper
├── LICENSE
├── README.md
└── imgs

@article{zhou2023learning,
title       = {Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling},
author      = {Jianan Zhou and Yaoxin Wu and Zhiguang Cao and Wen Song and Jie Zhang and Zhenghua Chen},
journal     = {IEEE Transactions on Knowledge and Data Engineering},
year        = {2023},
doi         = {10.1109/TKDE.2023.3249799},
publisher   = {IEEE}
}

@article{wu2023neural,
title       = {Neural Airport Ground Handling},
author      = {Yaoxin Wu and Jianan Zhou and Yunwen Xia and Xianli Zhang and Zhiguang Cao and Jie Zhang},
journal     = {IEEE Transactions on Intelligent Transportation Systems},
year        = {2023},
doi         = {10.1109/TITS.2023.3253552},
publisher   = {IEEE}
}