Abstract: In the process of Hardware/software co-design of spacecraft control computers, the multi-objective optimization is a key problem. The current strength Pareto evolutionary algorithm has some advantages in solving high-dimensional multi-objective optimization problems, but the computing time-complexity during the step of environmental selection is still very large. Aiming at this point, an improved algorithm was proposed. With the finite K-nearest neighbor method, new algorithm reduces the number of comparisons to lower the time-complexity from O(M3) down to O(max(l,logM)M2 . The experimental results show that the proposed algorithm not only improves the running speed, but also acquires better convergence and distribution diversity than the original one.

Key words: Hardware/software co-design, Multi-objective optimization, Pareto optimization, Strength Pareto evolutionary algorithm, On-board computer, Spacecraft control