2008 Eighth International Conference on Hybrid Intelligent Systems A Self-Adaptive Evolutionary Algorithm for Cluster Geometry Optimization September 10-September 12 ISBN: 978-0-7695-3326-1
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HIS.2008.96
We propose a self-adaptive hybrid evolutionary algorithm for the optimization of Morse clusters. The approach relies on a two-phase local optimization method to efficiently guide search. Individuals encode its own penalty settings and the algorithm evolves them simultaneously with the search for low energy clusters. Results show that the approach is efficient, as it is able to discover all optimal solutions for Morse clusters between 41 and 80 atoms.
Index Terms:
evolutionary computation, self-adaptation, cluster structure optimization
Citation:
Francisco B. Pereira, Jorge M.C. Marques, "A Self-Adaptive Evolutionary Algorithm for Cluster Geometry Optimization," his, pp.678-683, 2008 Eighth International Conference on Hybrid Intelligent Systems, 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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