Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm

@inproceedings{Mart2008IntroducingMS,
  title={Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm},
  author={Luis Mart{\'i} and Jes{\'u}s Caja Garc{\'i}a and Antonio Berlanga and Jos{\'e} M. Molina L{\'o}pez},
  booktitle={GECCO},
  year={2008}
}
In this paper we explore the model-building issue of multiobjective optimization estimation of distribution algorithms. We argue that model-building has some characteristics that differentiate it from other machine learning tasks. A novel algorithm called multiobjective neural estimation of distribution algorithm (MONEDA) is proposed to meet those characteristics. This algorithm uses a custom version of the growing neural gas (GNG) network specially meant for the model-building task. As part of… CONTINUE READING
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