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Article
MOEA/D with chain-based random local search for sparse optimization
The goal in sparse approximation is to find a sparse representation of a system. This can be done by minimizing a data-fitting term and a sparsity term at the same time. This sparse term imposes penalty for sp...
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Article
Combinations of estimation of distribution algorithms and other techniques
This paper summaries our recent work on combining estimation of distribution algorithms (EDA) and other techniques for solving hard search and optimization problems: a) guided mutation, an offspring generator ...