An Airport Gate Assignment Model by Considering Multiple Constraints Deriving from Business Rules

Abstract

Abstract Airport gate is the core resource for airport operation and organization, and thus an optimal airport gate assignment (AGA) schedule plays a critical role to ensure the high-efficiency airport operation. In this paper, considering the actual business rules of airport, the AGA problem is explored and a model based on the actual business rules of airport is established. The model aims to maximize the passenger docking rate and comprehensively considers several constraints deriving from business rules, such as the limitation of adjacent aircraft models, conflict of slide in and out and gate conflict restrictions. The actual business rules of airport are abstracted into the objective functions and constraints of the model. In view of the large-scale complicated combinational optimization problem deriving from the model, an improved immune genetic algorithm is designed to solve the model. Based on the traditional immune genetic algorithm, the proposed algorithm further integrates the variety of population, adaptive crossover probability and memory library to improve the solving efficiency. Moreover, a numerical experiment is designed by using the real-world data from Kunming Changshui International Airport. The experimental results indicate that the proposed model and algorithm have feasibility and effectiveness. The optimal assignment schedule has ability to increase the berth utilization ratio for both passengers and flights.