›› 2015, Vol. 35 ›› Issue (2): 49-.doi: 10.3780/j.issn.1000-758X.2015.02.007

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An Improved Strength Pareto Evolutionary Algorithm Based onthe Limited K-Nearest Neighbor Method

  

  1. (1 Beijing Institute of Control Engineering, Beijing 100190)(2 China Academy of Space Technology, Beijing 100094) (3 Science and Technology on Space Intelligent Control Laboratory, Beijing 100190)〖JZ)〗〖HQK〗
  • Online:2015-04-25 Published:2015-04-25

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