Multi-objective immune algorithm with Baldwinian learning

  title={Multi-objective immune algorithm with Baldwinian learning},
  author={Yutao Qi and Fang Liu and Meiyun Liu and Maoguo Gong and Licheng Jiao},
  journal={Appl. Soft Comput.},
By replacing the selection component, a well researched evolutionary algorithm for scalar optimization problems (SOPs) can be directly used to solve multi-objective optimization problems (MOPs). Therefore, in most of existing multi-objective evolutionary algorithms (MOEAs), selection and diversity maintenance have attracted a lot of research effort. However, conventional reproduction operators designed for SOPs might not be suitable for MOPs due to the different optima structures between them… CONTINUE READING
Highly Cited
This paper has 29 citations. REVIEW CITATIONS
14 Citations
22 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 14 extracted citations


Publications referenced by this paper.
Showing 1-10 of 22 references

A new local search strategy for memetic multiobjective evolutionary algorithms : HCS

  • G. Sanchez A. Lara, C. A. Coello Coello, O. Schütze
  • IEEE Transactions on Evolutionary Computation
  • 2010

Adaptive ranks and Knearest neighbour list based multiobjective immune algorithm

  • L. C. Jiao, M. G. Gong
  • NNIA , Evolutionary Computation
  • 2008

Improving the strength Pareto evolutionary algorithm for multi-objective optimization, Evolutionary Methods for Design, Optimisation and Control with Application to Industrial Problems

  • M. E. Zitzler, L. Laumanns, Thiele, SPEA
  • 2002
2 Excerpts

Similar Papers

Loading similar papers…