A surrogate model assisted evolutionary algorithm for computationally expensive design optimization problems with discrete variables

@article{Liu2016ASM,
  title={A surrogate model assisted evolutionary algorithm for computationally expensive design optimization problems with discrete variables},
  author={Bo Liu and Nan Sun and Qingfu Zhang and Vic Grout and Georges G. E. Gielen},
  journal={2016 IEEE Congress on Evolutionary Computation (CEC)},
  year={2016},
  pages={1650-1657}
}
Real-world computationally expensive design optimization problems with discrete variables pose challenges to surrogate-based optimization methods in terms of both efficiency and search ability. In this paper, a new method is introduced, called surrogate model-aware differential evolution with neighbourhood exploration, which has two phases. The first phase adopts a surrogate-based optimization method based on efficient surrogate model-aware search framework, the goal of which is to reach at… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 26 REFERENCES

The design and analysis of computer experiments

  • T. J. Santner, B. J. Williams, W. I. Notz
  • Springer
  • 2003
Highly Influential
3 Excerpts

A surrogate model algorithm for computationally expensive nonlinear mixed - integer black - box global optimization problems

  • C. A. Shoemaker Müller, R. Piché
  • Computers & Operations Research
  • 2013

An adaptive multiquadric radial basis function method for expensive black-box mixed-integer nonlinear constrained optimization

  • K. Rashid, S. Ambani, E. Cetinkaya
  • Engineering Optimization 45 (2)
  • 2013
3 Excerpts

Similar Papers

Loading similar papers…