Enhanced MaxCut Clustering with Multivalued Neural Networks and Functional Annealing
作者： Enrique Mérida Casermeiro , Domingo López-Rodríguez , Juan Miguel Ortiz-de-Lazcano-Lobato
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摘要: In this work a new algorithm to improve the performance of opti- mization methods, by means avoiding certain local optima, is described. Its theoretical bases are presented in rigorous, but intuitive, way. It has been ap- plied concretely case recurrent neural networks, particular MREM, multivalued model, that proved obtain very good results when dealing with NP-complete combinatorial optimization problems. order show its efficiency, well-known MaxCut problem for graphs selected as ben- chmark. Our proposal outperforms other specialized and powerful techniques, shown simulations.
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