A Novel Mission Planning Model and Method for Combat system-of-systems Architecture Design

The study of combat system-of-systems architecture design (CSAD) is the basis of cross-domain cooperative activities, and cross-domain cooperative activities are the basis for realizing mosaic warfare. This paper proposes a mixed-integer programming model for CSAD problem-oriented mission planning and an improved evolutionary algorithm for solving the model. The goal of the CSAD problem is to design the architecture of the combat system-of-systems which is evaluated based on the performance of combat tasks. Therefore, it is necessary to model the mission planning problem, and the model should fit the characteristic of the combat system-of-systems architecture. An improved evolutionary algorithm to solve the mission planning problem is proposed. To improve the solution effect, the task planning algorithm based on predecessor strategy was designed. To further improve the performance of mission planning algorithm, an elite retention strategy was proposed, so that it can retain more good individuals and delete more poor individuals during the evolution of the algorithm, so that the solution process of the planning solution converges as soon as possible. The simulation experiments show that the proposed method can solve the CSAD problem well and has a significant improvement effect compared with the comparative neighborhood search algorithm and two heuristic algorithms.