Title: Application of ant colony algorithm in the simulation-based approach to improve airport surface operations
Authors: Wenbin Wei; Lawrence Davis; Chunsheng Fu; Yanan Ding
Addresses: Department of Aviation and Technology, San Jose State University, One Washington Square, San Jose, CA 95192-0061, USA ' VGO Associates, 36 Low Street, Newbury, MA 01951, USA ' VGO Associates, 36 Low Street, Newbury, MA 01951, USA ' Human Automation Integration Lab (HAIL), San Jose State University, One Washington Square, San Jose, CA 95192, USA
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.
Keywords: airport surface operations; simulation; ant colony optimisation; ACO; Dallas-Fort Worth airport; airports; genetic algorithms; pushback scheduling; taxiway scheduling; runway assignment.
DOI: 10.1504/IJISE.2015.069549
International Journal of Industrial and Systems Engineering, 2015 Vol.20 No.2, pp.192 - 208
Published online: 23 May 2015 *
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