Abstract
In this paper we propose a new parallelization scheme for Simulated Annealing | Hierarchical Parallel SA (HPSA). This new scheme features coarse-granularity in parallelization, directed at message-passing systems such as clusters. It combines heuristics such as adaptive clustering with SA to achieve more efficiency in local search. Through experiments with various optimization problems and comparison with some available schemes, we show that HPSA is a powerful general-purposed optimization method. It can also serve as a framework for meta-heuristics to gain broader application.
This project is supported by NSFC 60273007.
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© 2005 Springer-Verlag Berlin Heidelberg
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Xu, S., Chen, W., Zheng, W., Wang, T., Zhang, Y. (2005). Hierarchical Parallel Simulated Annealing and Its Applications. In: Hobbs, M., Goscinski, A.M., Zhou, W. (eds) Distributed and Parallel Computing. ICA3PP 2005. Lecture Notes in Computer Science, vol 3719. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564621_33
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DOI: https://doi.org/10.1007/11564621_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29235-7
Online ISBN: 978-3-540-32071-5
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