Parallel two-level simulated annealing

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In this paper, we propose a new kind of simulated annealing algorithm called two-level simulated annealing for solving certain class of hard combinatorial optimization problems. This two-level simulated annealing algorithm is less likely to get stuck at a non-global minimizer than conventional simulated annealing algorithms. We also propose a parallel version of our two-level simulated annealing algorithm and discuss its efficiency. This new technique is then applied to the Molecular Conformation problem in 3 dimensional Euclidean space and implemented on the Thinking Machines CM-5. With the full Lennard-Jones potential function, we were able to get satisfactory results for clusters with as many as 100, 000 atoms. A peak rate of over 0.8 giga flop per second in 64-bit operations was sustained on a partition with 512 processing elements. To the best of our knowledge, ground states of Lennard-Jones clusters of as large as these have never been reported before.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th International Conference on Supercomputing, ICS 1993
PublisherAssociation for Computing Machinery
Pages357-366
Number of pages10
ISBN (Electronic)089791600X
DOIs
StatePublished - Aug 1 1993
Event7th International Conference on Supercomputing, ICS 1993 - Tokyo, Japan
Duration: Jul 19 1993Jul 23 1993

Publication series

NameProceedings of the International Conference on Supercomputing
VolumePart F129670

Other

Other7th International Conference on Supercomputing, ICS 1993
CountryJapan
CityTokyo
Period7/19/937/23/93

ASJC Scopus subject areas

  • Computer Science(all)

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    Xue, G. L. (1993). Parallel two-level simulated annealing. In Proceedings of the 7th International Conference on Supercomputing, ICS 1993 (pp. 357-366). (Proceedings of the International Conference on Supercomputing; Vol. Part F129670). Association for Computing Machinery. https://doi.org/10.1145/165939.166011