An Evolutionary Algorithm in Static Airport Gate Assignment Problem
Y. T. Chow1, Kam K.H. NG2, *, K. L. Keung3
Identifiers and Pagination:Year: 2022
E-location ID: e187444782203040
Publisher ID: e187444782203040
Article History:Received Date: 31/7/2021
Revision Received Date: 01/11/2021
Acceptance Date: 24/12/2021
Electronic publication date: 27/04/2022
Collection year: 2022
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background and Objectives:
Gate Assignment Problem is an existing issue at modern airports. Gate assignment is a complex issue in which different airports have their own demographic and geographic features although the gate and flight pattern are identical, and flights may not be assigned precisely to the gates.
The gate assignment model would be a suitable and an appropriate tool for airport authorities to assign aircraft to gates in an effective and efficient way. The aim of the model is to assign each aircraft to an available gate to maximise both efficient operations for airports and airlines, and convenience for passengers. The model would benefit airports by improving efficiency of operations and convenience for travellers. The model illustrates how the resources are fully utilised, achieving an optimal result. This model applies the evolutionary approach to handle the gate assignment problem. The smart and generative algorithm speeds up the solving process for providing the solution within a reasonable time.
This model can reduce the business class travellers’ total walking distance by optimising the utilisation of gate resources. This has been was applied at the Taiwan Taipei Taoyuan International Airport and the results have shown an improvement in minimising the total walking distances, and the results for business class travellers are promising.
A metropolitan airport usually handles more than thirty boarding gates and hundreds of flights every day. Gate assignment can help an airport to assign the gates to the flights more effectively, with the advancement of genetic algorithms. The gate assignment problem model performed a successful assignment solution within an acceptable timeframe. The proposed evolutionary algorithm gate assignment model could reduce the business class passengers’ total walking distances.