MB-GNG: Addressing drawbacks in multi-objective optimization estimation of distribution algorithms

Abstract

We examine the model-building issue related to multi-objective estimation of distribution algorithms (MOEDAs) and show that some of their, as yet overlooked, characteristics render most current MOEDAs unviable when addressing optimization problems with many objectives. We propose a novel modelbuilding growing neural gas (MB-GNG) network that is specially… (More)
DOI: 10.1016/j.orl.2011.01.002

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@article{Mart2011MBGNGAD, title={MB-GNG: Addressing drawbacks in multi-objective optimization estimation of distribution algorithms}, author={Luis Mart{\'i} and Jes{\'u}s Garc{\'i}a and Antonio Berlanga and Carlos A. Coello Coello and Jos{\'e} M. Molina L{\'o}pez}, journal={Oper. Res. Lett.}, year={2011}, volume={39}, pages={150-154} }