Abstract
This paper presents a novel hybrid algorithm for combinatorial optimization problems based on mixing the cross-entropy (CE) method and a Hopfield neural network. The algorithm uses the CE method as a global search procedure, whereas the Hopfield network is used to solve the constraints associated to the problems. We have shown the validity of our approach in several instance of the generalized frequency assignment problem. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Ortiz-García, E. G., & Pérez-Bellido, Á. M. (2007). Hybrid cross-entropy method/hopfield neural network for combinatorial optimization problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4881 LNCS, pp. 1160–1169). Springer Verlag. https://doi.org/10.1007/978-3-540-77226-2_116
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