A stopping criterion for multi-objective optimization evolutionary algorithms

@article{Mart2016ASC,
  title={A stopping criterion for multi-objective optimization evolutionary algorithms},
  author={Luis Mart{\'i} and Jes{\'u}s Caja Garc{\'i}a and Antonio Berlanga and Jos{\'e} M. Molina L{\'o}pez},
  journal={Inf. Sci.},
  year={2016},
  volume={367-368},
  pages={700-718}
}
This paper puts forward a comprehensive study of the design of global stopping criteria for multi-objective optimization. In this study we propose a global stopping criterion, which is terms as MGBM after the authors surnames. MGBM combines a novel progress indicator, called mutual domination rate (MDR) indicator, with a simplified Kalman filter, which is used for evidence-gathering purposes. The MDR indicator, which is also introduced, is a special-purpose progress indicator designed for the… CONTINUE READING

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