With the rapid development of drone technology, drone training has been widely applied in various fields such as military and civilian. The effective coordination of drones has become the most important task in complex missions. This study explores the application of multi-objective optimization in the decision-making process of drone training, with a particular focus on task allocation and route planning. Adopting NSGA-II, MOPSO, and MOSA to enhance the team’s ability to execute tasks. Experimental results have shown that the above methods can effectively improve the operational efficiency of the system, reduce energy consumption, and enhance safety. The research results of this project will help solve key issues such as UAV training decision-making process, improve operational efficiency and safety, and also provide theoretical and technical support for UAV collaborative training, which has important practical significance.