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 nextgeneration 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.