An interactive method for multi-satellite imaging mission planning in complex environments

Existing multi-satellite imaging mission planning methods mostly apply to scenarios with clear problem boundaries, explicit decision rules, and limited problem sizes. It is difficult to deal with the problem that the real environment is more complex and the action effect is more uncertain. This paper proposes a Human-machine interactive mechanism based on knowledge transfer strategy multi-objective evolutionary algorithm (HMIM-KTSMOEA) for Multi-satellite Imaging Mission Planning in Complex Environments (MSIMPCE). Firstly, a Human-machine interactive mechanism is proposed to deal with the dynamic changes of the environment effectively. Secondly, a multi-objective evolutionary algorithm based on a knowledge transfer strategy is proposed to improve the efficiency of MSIMPCE, which has complex constraints and large solving space. Simulation results show that HMIM-KTSMOEA has obvious advantages in solving the MSIMPCE problem in terms of task execution efficiency and response time.