Multi-start JADE with knowledge transfer for numerical optimization

  title={Multi-start JADE with knowledge transfer for numerical optimization},
  author={Fei Peng and Ke Tang and Guoliang Chen and Xin Yao},
  journal={2009 IEEE Congress on Evolutionary Computation},
JADE is a recent variant of Differential Evolution (DE) for numerical optimization, which has been reported to obtain some promising results in experimental study. However, we observed that the reliability, which is an important characteristic of stochastic algorithms, of JADE still needs to be improved. In this paper we apply two strategies together on the original JADE, to dedicatedly improve the reliability of it. We denote the new algorithm as rJADE. In rJADE, we first modify the control… CONTINUE READING
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