Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization

@article{Li2014ShiftBasedDE,
  title={Shift-Based Density Estimation for Pareto-Based Algorithms in Many-Objective Optimization},
  author={Miqing Li and Shengxiang Yang and Xiaohui Liu},
  journal={IEEE Transactions on Evolutionary Computation},
  year={2014},
  volume={18},
  pages={348-365}
}
It is commonly accepted that Pareto-based evolutionary multiobjective optimization (EMO) algorithms encounter difficulties in dealing with many-objective problems. In these algorithms, the ineffectiveness of the Pareto dominance relation for a high-dimensional space leads diversity maintenance mechanisms to play the leading role during the evolutionary process, while the preference of diversity maintenance mechanisms for individuals in sparse regions results in the final solutions distributed… CONTINUE READING
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