摘要
针对导弹集群协同作战的任务分配问题,提出了一种基于遗传算法的任务分配方法,提高了多任务组合优化问题的搜索能力。该方法采用一种任务组合编码的新方法,实现在整个解空间上寻找到最优组合问题的全局最优解或次优解。实验结果表明,本文方法能有效地解决导弹集群的任务分配问题,获得令人满意的实验结果。
To solve the problem of cooperative multiple task allocation for missile swarm, an improved genetic algorithm is proposed, which efficiently raises the searching ability for large scale combinatorial optimization problem. A global optimal solution or a inferior to optimal solution of the best combinatorial optimization problem can be abtained by combinatorial coding of mission. Experimental results demonstrated that this method can complete large-scale task allocation for missile swarm efficiently and promising results are obtained.
出处
《导弹与航天运载技术》
北大核心
2008年第5期39-42,共4页
Missiles and Space Vehicles
关键词
导弹集群
多任务分配
遗传算法
组合优化
Missile swarm
Multiple task allocation
Genetic algorithm
Combinatorial optimization
作者简介
严江江（1979-），男，博士生，研究方向为飞行器任务规划、图像处理等
