An ant colony optimisation method based on pruning technique for the aircraft arrival sequencing and scheduling problem Online publication date: Wed, 04-Jan-2017
by Xiaorong Feng; Xingjie Feng; Xinglong Wang
International Journal of Applied Decision Sciences (IJADS), Vol. 9, No. 4, 2016
Abstract: Aircraft arrival sequencing and scheduling (ASS) in civil aviation has become a critical concern which requires immediate attention. Pruning optimisation technique is a kind of important method to narrow the searching of candidate sets of the ASS problem. In this paper, an ant colony optimisation (ACO) algorithm based on pruning thought (termed PACO) is proposed. In the context of developing solutions to ASS problems, PACO is an improvement over traditional ant colony optimisation algorithm as it is empirically proven that PACO improves quality of solution by reducing computational burden and overcomes the problems of slow convergence speed. Experimental results show that the proposed method has stronger robustness, search ability and faster convergence rate compared with genetic and ant colony algorithm based on time-domain. It can help the traffic controllers for rapid, stable and fair scheduling.
Online publication date: Wed, 04-Jan-2017
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Applied Decision Sciences (IJADS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org