TY - GEN
T1 - Aircraft landing scheduling in the small aircraft transportation system
AU - Bai, Chongyang
AU - Zhang, Xuejun
PY - 2011
Y1 - 2011
N2 - Aircraft Scheduling in terminal areas is the key technology for diminishing delay and cost. Especially in SATS (Small Aircraft Transportation System), without the guidance of ATC (Air Traffic Control), efficiency is hard to reach. Considering diversity of aircrafts in SATS, traditional approaches to solve these problems, such as CPS (Constraint Position Switch) is not available. Promote to sequence aircrafts based on flying ability, and improve genetic algorithm by introduce local fitness value, using it as optimize function. Also, take vortex and conflict-free as the constraint. A potential algorithm is introduced to de-conflict for its ability to cover all possible conflict scenarios involving multiple agents. As a dynamic system, the cost of resolve conflict during the approach will feed back to the system to rescheduling. Simulation shows, a conflict-free sequence with lower delay is reached. Besides, the improved algorithm is more directive and convergence quickly, accelerating solving process. It can meet the application's needs in real-time.
AB - Aircraft Scheduling in terminal areas is the key technology for diminishing delay and cost. Especially in SATS (Small Aircraft Transportation System), without the guidance of ATC (Air Traffic Control), efficiency is hard to reach. Considering diversity of aircrafts in SATS, traditional approaches to solve these problems, such as CPS (Constraint Position Switch) is not available. Promote to sequence aircrafts based on flying ability, and improve genetic algorithm by introduce local fitness value, using it as optimize function. Also, take vortex and conflict-free as the constraint. A potential algorithm is introduced to de-conflict for its ability to cover all possible conflict scenarios involving multiple agents. As a dynamic system, the cost of resolve conflict during the approach will feed back to the system to rescheduling. Simulation shows, a conflict-free sequence with lower delay is reached. Besides, the improved algorithm is more directive and convergence quickly, accelerating solving process. It can meet the application's needs in real-time.
KW - conflict
KW - genetic algorithm
KW - landing
KW - SATS
KW - scheduling
UR - https://www.scopus.com/pages/publications/83755163533
U2 - 10.1109/ICCIS.2011.65
DO - 10.1109/ICCIS.2011.65
M3 - 会议稿件
AN - SCOPUS:83755163533
SN - 9780769545011
T3 - Proceedings - 2011 International Conference on Computational and Information Sciences, ICCIS 2011
SP - 1019
EP - 1022
BT - Proceedings - 2011 International Conference on Computational and Information Sciences, ICCIS 2011
T2 - 2011 International Conference on Computational and Information Sciences, ICCIS 2011
Y2 - 21 October 2011 through 23 October 2011
ER -