Generalized simulated annealing algorithm and its application to the Thomson model |
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| Institution: | 1. Microsoft Research, Haifa, Israel;2. Electrical Engineering Department, Tel Aviv University, Tel Aviv, Israel;3. Microsoft Research, Redmond, WA, USA;1. Department of Functional Morphology and Biomechanics, Kiel University, Am Botanischen Garten 9, D-24118 Kiel, Germany;2. Donetsk Institute for Physics and Engineering, National Academy of Sciences of Ukraine, Donetsk, Ukraine;3. Behavioural Ecology, Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia;4. Department of Integrative Zoology, University of Vienna, Faculty of Life Science, Althanstrasse 14, 1090 Vienna, Austria |
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| Abstract: | Based on the Tsallis statistics, the generalized simulated annealing algorithm (GSA) is tested and developed. Studies on the Thomson model show that the GSA is more efficient than the classical simulated annealing and the fast simulated annealing. The fluctuation of energy is reduced drastically. The convergence to the global minimum is fast. We believe the GSA algorithm is a powerful method to find the global minimum in more realistic problems, like the equilibrium structure of big clusters. |
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