Research on UAV Forest Fire Prevention Patrol Path Based on Hybrid Genetic Algorithm
This study proposes a hybrid genetic algorithm that combines K-means clustering analysis with a simulated annealing-improved genetic al-gorithm to optimize UAV forest fire prevention patrol paths.First,K-means clustering analysis is used to classify patrol points,effectively reducing the solution space and accommodating the UAV's range limitations.Then,the initial population is encoded using natural numbers to represent each patrol point,forming the initial solution set.In the evolutionary mechanism,an improved Order Crossover(OX)technique is used for gene exchange,and the selection operation is optimized with simulated annealing to enhance local search capability and prevent premature convergence.Using Lakou Town in Qingtian County,Zhejiang Province,as an example,empirical results show that K-means clustering divides the patrol points into two clusters,and the improved genetic algorithm optimizes each cluster,achieving global optimal solutions.Simulation results indicate that the improved hybrid genetic al-gorithm performs excellently in patrol path planning for different scales of patrol points:when the number of patrol points is less than 10,there is no significant difference between the traditional and hybrid genetic algorithms;however,when the number of patrol points exceeds 20,the hybrid genetic algorithm shows a clear advantage.For 30 patrol points,optimization time increased by approximately 3.37 seconds,but the optimal path length de-creased by 23.90%.For 40 patrol points,optimization time increased by about 4.83 seconds,but the optimal path length decreased by 30.18%.The conclusions show that K-means clustering effectively reduces the solution space and accommodates UAV range limitations,while the combination of the genetic algorithm's global search and simulated annealing's local search significantly enhances UAV patrol efficiency and resource allocation,pro-viding new insights for the application of UAVs in forest fire prevention.
Genetic AlgorithmK-means Clustering AlgorithmUAVForest Fire PreventionPath Planning
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