Reply to J. Vrugt's comment on "How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?"

@inproceedings{Reed2007ReplyTJ,
  title={Reply to J. Vrugt's comment on "How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration?"},
  author={Patrick M. Reed and Yong Tang and Thorsten Wagener},
  year={2007}
}
This study provides a comprehensive assessment of state-of-the-art evolutionary multiobjective optimization (EMO) tools’ relative effectiveness in calibrating hydrologic models. The relative computational efficiency, accuracy, and ease-of-use of the following EMO algorithms are tested: Epsilon Dominance Nondominated Sorted Genetic AlgorithmII (ε-NSGAII), the Multiobjective Shuffled Complex Evolution Metropolis algorithm (MOSCEM-UA), and the Strength Pareto Evolutionary Algorithm 2 (SPEA2). This… CONTINUE READING

Similar Papers

References

Publications referenced by this paper.
SHOWING 1-10 OF 64 REFERENCES

The Value of Online Adaptive Search: A comparison of NSGA-II,ε-NSGAII, andε MOEA, in: Evolutionary Multi Criterion Optimization: Third International Conference (EMO

J. B. Kollat, P. Reed
  • 2005
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

Evolutionary Algorithms for Solving Multi-Objective Problems

  • Genetic Algorithms and Evolutionary Computation
  • 2002
VIEW 11 EXCERPTS
HIGHLY INFLUENTIAL

Multi-Objective Optimization using Evolutionary Algorithms

K. Deb
  • 2001
VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II

K. Deb, A. Pratap, S. Agarwal, T. Meyarivan
  • IEEE Trans. Evol. Computation,
  • 2002
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

Scalable multi-objective optimization test problems

  • Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)
  • 2002
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL