Multi-strategy particle swarm and ant colony hybrid optimization for airport taxiway planning problem

被引:121
作者
Deng, Wu [1 ,2 ]
Zhang, Lirong [1 ]
Zhou, Xiangbing [2 ]
Zhou, Yongquan [4 ]
Sun, Yuzhu [3 ]
Zhu, Weihong [3 ]
Chen, Huayue [5 ]
Deng, Wuquan [6 ]
Chen, Huiling [7 ]
Zhao, Huimin [1 ]
机构
[1] Civil Aviat Univ China, Sch Elect Informat & Automat, Tianjin 300300, Peoples R China
[2] Sichuan Tourism Univ, Sch Informat & Engn, Chengdu 610100, Peoples R China
[3] Shenzhen Airlines Co Ltd, Shenzhen 518128, Peoples R China
[4] Guangxi Univ Nationalities, Coll Artificial Intelligence, Nanning 530006, Peoples R China
[5] China West Normal Univ, Sch Comp Sci, Nanchong 637002, Peoples R China
[6] Chongqing Univ, Cent Hosp, Dept Endocrinol, Key Lab Biorheol Sci & Technol,Minist Educ, Chongqing 400014, Peoples R China
[7] Wenzhou Univ, Key Lab Intelligent Image Proc & Anal, Wenzhou 325035, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Ant colony optimozation; Particle swarm optimozation; Pheromone hybrid strategy; First come and first serve; Multi-strategy; Taxiway planning; ALGORITHM;
D O I
10.1016/j.ins.2022.08.115
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As the connecting hub of the airport runways and gates, the taxiway plays a very important role in the rational allocation and utilization of the airport resources. In this paper, a multi -strategy particle swarm and ant colony hybrid optimization algorithm, namely MPSACO is proposed to solve the airport runway planning problem and avoid taxiway conflicts and conflict propagation. Firstly, a reasonable mathematical model of airport taxiway planning is constructed. Secondly, the multi-strategy particle swarm optimization algorithm (CWBPSO) is employed to propose a new pheromone initialization approach for ACO. And a new pheromone allocation mechanism is designed and a new pheromone update strategy based on the principle of wolf predation is developed, which are combined to design a new pheromone hybrid strategy to enhance the pheromone influence of the opti-mal solution, dynamically adjust the search direction, and avoid to decline the best search ability, so as to greatly improve the optimization performance of the algorithm. Finally, an airport taxiway planning approach based on MPSACO is proposed, and a conflict adjust-ment strategy based on speed priority and the idea of first come and first serve (FCFS) is designed to effectively optimize the airport taxiway path. In order to prove the effective-ness of the proposed algorithm/method, 10 traveling salesman problems (TSP) with differ-ent scales and an actual airport taxiway planning problem are selected in here. The experiment results show that the proposed MPSACO can effectively solve TSP and obtain the better optimal solutions, and the proposed airport taxiway planning approach can effectively plan the airport taxiing path, avoid the airport taxiing conflicts, and improve the utilization rate of taxiway resources.(c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码:576 / 593
页数:18
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