Considering the optimal planning of tactical actions sequences, a tactical mission planning algorithm based on hierarchical task network (HTN) and genetic algorithms (GA) is proposed by integrating the qualitative knowledge and quantitative optimization. The HTN is used to model the tactic procedure knowledge on certain task, and then, GA is applied to optimize the tactic procedure knowledge so that the best tactic can be searched and selected. The sound and complete procedure for HTN_ GA tactic planning are analyzed. The UCAV tactic planning algorithm for suppress enemy air defense (SEAD) based on the proposed HTN_GA is presented. The simulation results demonstrate feasibility of the proposed tactic mission plan algorithm.