Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77717
Title: Review on meta-heuristics approaches for airside operation research
Authors: Ng, KKH 
Lee, CKM 
Chan, FTS 
Lv, Y
Keywords: Airside operation
Aviation
Classification framework
Literature review
Meta-heuristics
Issue Date: 2018
Publisher: Elsevier
Source: Applied soft computing, 2018, v. 66, p. 104-133 How to cite?
Journal: Applied soft computing 
Abstract: The number of publications related to airside operation research is increasing and gaining in popularity. This paper aims to provide researchers with a comprehensive and extensive overview of meta-heuristics application for aviation research, with a particular focus on the airside operations. The scope of airside operation research covers airspace and air traffic flow management, aircraft operation in the terminal manoeuvring area and surface traffic operation. Based on the recent publications related to airside operations, the meta-heuristics approach is a promising approach to enhance the computational efficiency and achieve higher applicable in various decisions in airside operations. However, the literature on airside operation research is quite disjointed and disparate. Therefore, a general taxonomy framework for the airside information system is proposed in order to classify the research systematically and expedites related research and development of engineering applications in the aviation industry. To the best of our knowledge, this is the first review of the field using the meta-heuristics approach. The prominent findings of recent publication and the directions of future research are addressed throughout the review and analysis of the relevant studies.
URI: http://hdl.handle.net/10397/77717
ISSN: 1568-4946
EISSN: 1872-9681
DOI: 10.1016/j.asoc.2018.02.013
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