摘要
针对飞机战术飞行要求和威胁规避目标的问题,采用优势函数和战术规避相结合的原则,将战术航段优化问题转化为路径搜索问题,提出了基于多智能体遗传算法来解决此问题。采用自适应交叉和变异算子,改进自学习算子获取子代的算法,实现了全局最优的结果。通过和传统遗传算法进行仿真比较,相比之下,基于多智能体的遗传算法可以有效利用地形,实现战术飞行。
Aiming at demand of tactical flight and problem of threating avoidance target in airplane route planning, using principle combining advantage function with tactics avoidance, tactical segment optimization problem is turned into path searching issue, propose a tactical segment optimization method based on multi-agent genetic algorithm. By adopting self-adaptive crossing and mutation operator, improve algorithm which acquirs next- generation by self-learning operator , achieve global optimal result. Simulation results show that compared with traditional ones the improved genetic algorithm can effectively use terrain to fulfill tactical flight tasks.
出处
《传感器与微系统》
CSCD
2016年第3期40-43,48,共5页
Transducer and Microsystem Technologies
关键词
战术优化
多智能体
遗传算法
tactical optimization
multi-agent
genetic algorithm
