Modelling and sequencing of air traffic using genetic algorithm

Abstract

The Asia Pacific region is experiencing one of the fastest rates of air traffic growth in the world and projections show that this is set to continue in the long term. In order to maximize its full air traffic capacity potential, several measures have to been undertaken to support the anticipated growth and one crucial method is to enhance efficiency in air traffic management.

The aim of this study is to further develop an existing algorithm known as Genetic Algorithm (GA) to optimize the sequence of aircraft departing and arriving at Changi Airport Terminal 2. Under the previous study, an initial programme was set up and used to simulate 20 aircraft scenario with position shift constraint. After several rounds of modification and improvement, the results were satisfactory.

However, the limitation lies in the lack of responsiveness to dynamic situations and the variations of the problems were not discussed (delays, cancellation, route changes). This project serves to provide an in-depth analysis into the different kind of situations that could result in delays and a random generator was used prior to running the GA program to simulate the unplanned nature of flight cancellations and delays. The program was able to continue simulation by doing the appropriate shifts and providing the best possible timings after the situations were incorporated.