Airport Gate Assignment Problem considering Connecting Passengers

被引:0
作者
Wen, Ke [1 ]
He, Yongyi [1 ]
机构
[1] Shanghai Univ, Dept Serv Robot Lab, Shanghai, Peoples R China
来源
PROCEEDINGS OF 2020 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS) | 2020年
关键词
AGAP; connecting passenger; genetic algorithm; Multi-objective optimization model; OPTIMIZATION; MODEL;
D O I
10.1109/icaiis49377.2020.9194926
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the development of the air transport industry, many airports expanding the layout to increase the gates number. However, larger airports will increase the distance traveled by passengers at the airport, which is likely to cause connecting passengers to be unable to transfer in time due to the long distance. An efficient gate assignment method is necessary to solve the problem. We make two optimization models, aims to improve gate utilization and reduce connection time for connecting passengers. Considering that the airport gate assignment problem (AGAP) is NP-hard, we use genetic algorithms with data preprocessing (DP-GA) to solve the problem. We test the models and the algorithms on real data from PEK Airport to verify the effectiveness and efficiency of the algorithms.
引用
收藏
页码:248 / 254
页数:7
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