：为了保证无人作战飞机(UCAV)以最小的被发现概率和最优的航程到达目标点，在敌方防御区域内执

行任务前必须进行航路规划。蚁群优化(ACO)算法的并行实现机制适合于复杂作战环境下的UCAV航路规划，但是基本ACO算法有易陷于局部最优解的缺点-Abstract：To ensure unmanned combat aerial vehicle(UCAV)to reach the destination with an optimal path and a

minimum rate to be foun d，UCAV path plan ing must be ma de before mission execution．The parallelism of an t colony

optimization(ACO)is feasible in UCAV path planning under complicated combat environments