A Review of Constrained Multi-Objective Evolutionary Algorithm-Based Unmanned Aerial Vehicle Mission Planning: Key Techniques and Challenges

UAV mission planning is one of the core problems in the field of UAV applications. Currently, mission planning needs to simultaneously optimize multiple conflicting objectives and take into account multiple mutually coupled constraints, and traditional optimization algorithms struggle to effectively...

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Vydáno v:Drones (Basel) Ročník 8; číslo 7; s. 316
Hlavní autoři: Huang, Gang, Hu, Min, Yang, Xueying, Wang, Xun, Wang, Yijun, Huang, Feiyao
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.07.2024
Témata:
Algorithms
Business metrics
Classification
conflicting objectives
constrained multi-objective evolutionary algorithms
constraint handling techniques
Constraints
Control systems
Drone aircraft
Efficiency
Energy consumption
Evolutionary algorithms
Genetic algorithms
Mathematical models
Mathematical optimization
Methods
Mission planning
Multiple objective analysis
Optimization
Optimization algorithms
Optimization techniques
Planning
Real time
UAV mission planning
Unmanned aerial vehicles
China
ISSN:2504-446X, 2504-446X
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Abstract UAV mission planning is one of the core problems in the field of UAV applications. Currently, mission planning needs to simultaneously optimize multiple conflicting objectives and take into account multiple mutually coupled constraints, and traditional optimization algorithms struggle to effectively address these difficulties. Constrained multi-objective evolutionary algorithms have been proven to be effective methods for solving complex constrained multi-objective optimization problems and have been gradually applied to UAV mission planning. However, recent advances in this area have not been summarized. Therefore, this paper provides a comprehensive overview of this topic, first introducing the basic classification of UAV mission planning and its applications in different fields, proposing a new classification method based on the priorities of objectives and constraints, and describing the constraints of UAV mission planning from the perspectives of mathematical models and planning algorithms. Then, the importance of constraint handling techniques in UAV mission planning and their advantages and disadvantages are analyzed in detail, and the methods for determining individual settings in multiple populations and improvement strategies in constraint evolution algorithms are discussed. Finally, the method from the related literature is presented to compare in detail the application weights of constrained multi-objective evolutionary algorithms in UAV mission planning and provide directions and references for future research.
AbstractList UAV mission planning is one of the core problems in the field of UAV applications. Currently, mission planning needs to simultaneously optimize multiple conflicting objectives and take into account multiple mutually coupled constraints, and traditional optimization algorithms struggle to effectively address these difficulties. Constrained multi-objective evolutionary algorithms have been proven to be effective methods for solving complex constrained multi-objective optimization problems and have been gradually applied to UAV mission planning. However, recent advances in this area have not been summarized. Therefore, this paper provides a comprehensive overview of this topic, first introducing the basic classification of UAV mission planning and its applications in different fields, proposing a new classification method based on the priorities of objectives and constraints, and describing the constraints of UAV mission planning from the perspectives of mathematical models and planning algorithms. Then, the importance of constraint handling techniques in UAV mission planning and their advantages and disadvantages are analyzed in detail, and the methods for determining individual settings in multiple populations and improvement strategies in constraint evolution algorithms are discussed. Finally, the method from the related literature is presented to compare in detail the application weights of constrained multi-objective evolutionary algorithms in UAV mission planning and provide directions and references for future research.
Audience Academic
Author Hu, Min
Huang, Gang
Wang, Xun
Yang, Xueying
Huang, Feiyao
Wang, Yijun
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  surname: Huang
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  givenname: Xueying
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  surname: Yang
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  givenname: Xun
  surname: Wang
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  givenname: Yijun
  surname: Wang
  fullname: Wang, Yijun
– sequence: 6
  givenname: Feiyao
  surname: Huang
  fullname: Huang, Feiyao
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Snippet UAV mission planning is one of the core problems in the field of UAV applications. Currently, mission planning needs to simultaneously optimize multiple...
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SubjectTerms Algorithms
Business metrics
Classification
conflicting objectives
constrained multi-objective evolutionary algorithms
constraint handling techniques
Constraints
Control systems
Drone aircraft
Efficiency
Energy consumption
Evolutionary algorithms
Genetic algorithms
Mathematical models
Mathematical optimization
Methods
Mission planning
Multiple objective analysis
Optimization
Optimization algorithms
Optimization techniques
Planning
Real time
UAV mission planning
Unmanned aerial vehicles
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Title A Review of Constrained Multi-Objective Evolutionary Algorithm-Based Unmanned Aerial Vehicle Mission Planning: Key Techniques and Challenges
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