Confronting the situation of uneven educational background, knowledge comprehension and master speed of soldiers, stereotype education system of soldier's occupational skill no longer adapts the demand of network era development and informational military construction. The paper puts forward to the tactic of dynamically call ant algorithm and genetic algorithm according to the best fusion point after analyzing the existing problems in soldier's occupational skill education and the features of ant algorithm and genetic algorithm, so as to urge the optimization results of ant algorithm to optimize the initializing population of genetic algorithm. In addition, in order to find the personalized learning path suited to every soldier, the personalized learning process of soldiers is transformed into a typical combinatorial optimization problem successfully by imitating traveling salesman problem. The experiment results show that the convergence rate and optimization capability of the improved ant colony genetic algorithm is greatly improved.