Equipment battlefield repair is an important part of equipment support work. Traditional equipment battlefield repair has not met the needs of modern warfare. To improve the scientific and decision-making efficiency of equipment battlefield repair under information conditions， a generalized stochastic Petri net （GSPN） is used to model and analyze the equipment battlefield repair process， and the validity of the model is judged by invariants. According to the isomorphism characteristics of the generalized stochastic Petri net and Markov chain （ MC ）， the main performance indexes of the model are solved. Finally， through the example analysis， this method can effectively solve the main performance indexes of equipment battlefield repair， verify the validity and rationality of the model， and also provide a certain reference for equipment battlefield repair decisions.

The key to promoting the high-quality development of equipment is to strengthen the joint force of cross-organizational quality management between the military and local systems. Therefore， the coupling coordination relationship between them is studied in this paper. Since the traditional coupling coordination model only calculates the overall effectiveness of each indicator in the subsystem and ignores the impact of the interaction between indicators and between indicators and subsystems on the overall coupling effect， the method of combining the sustainable development system （SDS） coordinated development model with the coupling coordination model is adopted. When the coupling degree is calculated， the overall impact of other subsystems on each subsystem index is included， and the overall coupling coordination degree is measured more scientifically and comprehensively. Finally， the feasibility of this method is verified through an example.

Multi-missile coordination is a hot research direction of missile weapons with high research value， and how to plan the flight trajectory of multiple missiles is an important research content. In this paper， a multi-ballistic trajectory simulation method based on a multi-objective evolutionary algorithm based on decomposition （MOEA/D） algorithm is proposed， which takes the glide phase of boost glide missile as the research object and aims at planning multiple high-quality trajectories. The maximum range and the maximum final velocity are selected as the objective functions to realize the trajectory planning of the glide phase. Meanwhile， in order to reduce the impact of the initial population on the multi-objective optimization problem， the pseudo-spectral method is used to provide high-quality initial populations for the multi-objective optimization algorithm. The simulation results show that the method can obtain multi-ballistic trajectories with optimal range and final velocity.