Aviation Conflict Mediation Model Based on Dynamic Particle Swarm Algorithm

With the increasing demand of air transportation, various types of aircrafts and transport planes often need to be deployed at the same time and space, which leads to the contradiction between the surge of air demand and the limited airspace resources. This paper relies on the improved dynamic parti...

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Published in:2023 3rd International Signal Processing, Communications and Engineering Management Conference (ISPCEM) pp. 750 - 752
Main Authors: Tu, Yonglin, Xu, Haoli, Yang, Xing, Lu, Yun, Mu, Hua, Wang, Yangyang, Zhang, Chi, Liu, Xinyue, Gao, Xinglong, Zhang, Zhaoxin
Format: Conference Proceeding
Language:English
Published: IEEE 25.11.2023
Subjects:
Aircraft
Atmospheric modeling
aviation flight conflict
conflict resolution model
dynamic particle swarm optimization algorithm
Engineering management
Heuristic algorithms
Mediation
Particle swarm optimization
Signal processing algorithms
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Abstract With the increasing demand of air transportation, various types of aircrafts and transport planes often need to be deployed at the same time and space, which leads to the contradiction between the surge of air demand and the limited airspace resources. This paper relies on the improved dynamic particle optimization algorithm to establish a relief model for regulating the contradiction of airspace demand of various aircrafts, and experimentally verifies the feasibility and advantages of the model, and simulates the mediation of hundreds of conflicting airspace demands. The model can achieve global optimization between small fitness differences, and the optimization of the scheme can be achieved with a very small number of iterations. It provides a referable solution for problems with multiple local optimal solutions and complex nonlinear problems.
AbstractList With the increasing demand of air transportation, various types of aircrafts and transport planes often need to be deployed at the same time and space, which leads to the contradiction between the surge of air demand and the limited airspace resources. This paper relies on the improved dynamic particle optimization algorithm to establish a relief model for regulating the contradiction of airspace demand of various aircrafts, and experimentally verifies the feasibility and advantages of the model, and simulates the mediation of hundreds of conflicting airspace demands. The model can achieve global optimization between small fitness differences, and the optimization of the scheme can be achieved with a very small number of iterations. It provides a referable solution for problems with multiple local optimal solutions and complex nonlinear problems.
Author Wang, Yangyang
Zhang, Zhaoxin
Xu, Haoli
Yang, Xing
Liu, Xinyue
Lu, Yun
Zhang, Chi
Gao, Xinglong
Tu, Yonglin
Mu, Hua
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  givenname: Haoli
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  givenname: Xing
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  givenname: Yangyang
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  givenname: Chi
  surname: Zhang
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  organization: College of Electronic Countermeasures, National University of Defense Technology,State Key Laboratory of Pulsed Power Laser,Hefei,China,230037
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  givenname: Xinyue
  surname: Liu
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  organization: College of Electronic Countermeasures, National University of Defense Technology,State Key Laboratory of Pulsed Power Laser,Hefei,China,230037
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  givenname: Xinglong
  surname: Gao
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  organization: College of Electronic Countermeasures, National University of Defense Technology,State Key Laboratory of Pulsed Power Laser,Hefei,China,230037
– sequence: 10
  givenname: Zhaoxin
  surname: Zhang
  fullname: Zhang, Zhaoxin
  email: xcyb182@163.com
  organization: College of Electronic Countermeasures, National University of Defense Technology,State Key Laboratory of Pulsed Power Laser,Hefei,China,230037
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Snippet With the increasing demand of air transportation, various types of aircrafts and transport planes often need to be deployed at the same time and space, which...
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SubjectTerms Aircraft
Atmospheric modeling
aviation flight conflict
conflict resolution model
dynamic particle swarm optimization algorithm
Engineering management
Heuristic algorithms
Mediation
Particle swarm optimization
Signal processing algorithms
Title Aviation Conflict Mediation Model Based on Dynamic Particle Swarm Algorithm
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