Multi-Aircraft Coordinated Target Assignment Based on Chaotic Mutation Adaptive Salp Swarm Algorithm

Target assignment is a core issue in command and control, aiming to rationally distribute targets among multiple coordinated operational units based on battlefield conditions to maximize overall operational effectiveness. This study proposes a target assignment method based on a modified salp swarm algorithm to enhance the effectiveness of such coordinated operations. The research methodology is structured as follows. First, the method is based on the situational advantage of an operation in single-aircraft confrontation and the target threat assessment model and considers the coordination correlation between aircraft to establish a multi-aircraft coordinated situational advantage model. Second, a search strategy with a contraction mechanism and a combined mutation strategy is introduced to improve the search and development capabilities of the algorithm, and an adaptive inertia weight factor is designed to balance the search and development capabilities of the algorithm. Third, the multiple constraints inherent in target assignment are converted into the algorithm’s gain terms using a penalty function approach. Finally, simulation experiments were designed to verify the static, dynamic, and complex examples. The examples used in this study were compared with three algorithms in the literature in terms of their ability to solve multi-aircraft coordinated target assignment problems. The simulation results demonstrate that the modified salp swarm algorithm is well-suited for this problem, exhibiting convergent and stable behavior, a significantly improved fitness value, and the ability to optimize the target assignment scheme. This confirms the algorithm’s substantial utility in addressing the coordinated target assignment challenge.