Application of ant colony algorithm in the simulation–based approach to improve airport surface operations. (2015)

• Record Type: Journal Article
• Authors: Wei, Wenbin; Davis, Lawrence; Fu, Chunsheng; Ding, Yanan
• Is Part Of: International journal of industrial and systems engineering. Volume 20:Number 2(2015)
• Page Start: 192
• Page End: 208
• Publication Date: 2015
• Subjects: airport surface operations -- simulation -- ant colony optimisation -- ACO -- Dallas–Fort Worth airport -- airports -- genetic algorithms -- pushback scheduling -- taxiway scheduling -- runway assignment; Systems engineering -- Periodicals; Industrial engineering -- Periodicals; 620.001171
• Languages: English
• ISSNs: 1748-5037

Abstract

In this paper, we apply the ant colony algorithm in the optimiser for the simulation–based optimisation approach to improve airport surface operations. The major components of the system architecture and detailed descriptions of the implementations of the ant colony algorithm are introduced. The proposed ant colony algorithm and the simulation–based optimisation approach are applied to the case studies of the east side of the Dallas–Fort Worth airport (DFW). The initial results have demonstrated the success and benefit of applying the ant colony algorithm in the simulation–based approach for improving airport surface operations. The results have also implied that applying the combined genetic algorithm and ant colony algorithm in the optimiser can derive better results than using any one of the two algorithms solely.