首页
>
期刊首页
>
系统工程与电子技术（英文版）
>
2026年4期
>
A fast scheduling method of multiple agile satellites based on neural network-guided genetic algorithm
A fast scheduling method of multiple agile satellites based on neural network-guided genetic algorithm
摘要
Agile imaging satellites play important roles in gather-ing Earth surface information due to their expansive field-of-view,high-resolution observations,and flexibility in observation timing.Genetic algorithm(GA)has been one of the most com-monly utilized meta-heuristic algorithms for solving multiple agile satellites(MAS)scheduling problems due to its stable and good performance.Nonetheless,the iterative convergence speed of GA is slow owing to the blindness of the preliminary search.To address this issue,this paper proposes an efficient meta-heuris-tic MAS scheduling method integrated with a neural network(NN).In the proposed method,an NN is applied to learn the his-torical scheduling experience and generate effective initial solu-tions,thereby improving the convergence speed of GA for MAS scheduling.Experimental results demonstrate that the proposed NN-guided GA(NN-GA)accelerates the convergence of GA by approximately 60%and exhibits higher efficiency for MAS scheduling compared to existing state-of-the-art methods.
年，卷(期)：
2026, 37(4)
机标分类号：
TN925.93
S
TP391.41
在线出版日期：
2026年9月10日
