Control Application Based on Multi-objective Simulated Annealing Algorithm

The application of drones is a recent hot research topic. We need to use drones based on some optimization algorithms to find the best path for simulation data. We will use Monte Carol to simulate the initial solution to establish a multiobjective simulated annealing algorithm to arrange the UAV and...

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Published in:2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI) pp. 708 - 714
Main Authors: Wang, Xiang, Lu, Guanyu, Lu, Mingyu, Liu, Jiajun
Format: Conference Proceeding
Language:English
Published: IEEE 24.09.2021
Subjects:
component
Costs
GIS
MTSP (multiple traveling salesman problem)
Predictive models
Resource management
Safety
Sensitivity analysis
Simulated annealing
Traveling salesman problems
UAV
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Abstract The application of drones is a recent hot research topic. We need to use drones based on some optimization algorithms to find the best path for simulation data. We will use Monte Carol to simulate the initial solution to establish a multiobjective simulated annealing algorithm to arrange the UAV and balance two main goals: safety and cost. We also use other factors as parameters, including the size and frequency of the destination. We applied the algorithm to the simulated data and got the solution result. In addition, we conducted a sensitivity analysis on the outer loop parameters of the simulated annealing algorithm. At the same time, the model was evaluated, and its development prospects were forecasted.
AbstractList The application of drones is a recent hot research topic. We need to use drones based on some optimization algorithms to find the best path for simulation data. We will use Monte Carol to simulate the initial solution to establish a multiobjective simulated annealing algorithm to arrange the UAV and balance two main goals: safety and cost. We also use other factors as parameters, including the size and frequency of the destination. We applied the algorithm to the simulated data and got the solution result. In addition, we conducted a sensitivity analysis on the outer loop parameters of the simulated annealing algorithm. At the same time, the model was evaluated, and its development prospects were forecasted.
Author Wang, Xiang
Lu, Mingyu
Lu, Guanyu
Liu, Jiajun
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  surname: Lu
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  givenname: Jiajun
  surname: Liu
  fullname: Liu, Jiajun
  organization: School of Science, Xi'an Jiaotong-Liverpool University,Suzhou,China
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Snippet The application of drones is a recent hot research topic. We need to use drones based on some optimization algorithms to find the best path for simulation...
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SubjectTerms component
Costs
GIS
MTSP (multiple traveling salesman problem)
Predictive models
Resource management
Safety
Sensitivity analysis
Simulated annealing
Traveling salesman problems
UAV
Title Control Application Based on Multi-objective Simulated Annealing Algorithm
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