Genetic algorithm optimization of atomic clusters

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The authors have been using genetic algorithms to study the structures of atomic clusters and related problems. This is a problem where local minima are easy to locate, but barriers between the many minima are large, and the number of minima prohibit a systematic search. They use a novel mating algorithm that preserves some of the geometrical relationship between atoms, in order to ensure that the resultant structures are likely to inherit the best features of the parent clusters. Using this approach, they have been able to find lower energy structures than had been previously obtained. Most recently, they have ... continued below

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10 p.

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Morris, J.R.; Deaven, D.M.; Ho, K.M.; Wang, C.Z.; Pan, B.C.; Wacker, J.G. et al. December 31, 1996.

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  • Ames Laboratory
    Publisher Info: Ames Lab., IA (United States)
    Place of Publication: Iowa

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Description

The authors have been using genetic algorithms to study the structures of atomic clusters and related problems. This is a problem where local minima are easy to locate, but barriers between the many minima are large, and the number of minima prohibit a systematic search. They use a novel mating algorithm that preserves some of the geometrical relationship between atoms, in order to ensure that the resultant structures are likely to inherit the best features of the parent clusters. Using this approach, they have been able to find lower energy structures than had been previously obtained. Most recently, they have been able to turn around the building block idea, using optimized structures from the GA to learn about systematic structural trends. They believe that an effective GA can help provide such heuristic information, and (conversely) that such information can be introduced back into the algorithm to assist in the search process.

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10 p.

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INIS; OSTI as DE97006804

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  • IMA meeting on evolutionary algorithms, Minneapolis, MN (United States), 21-25 Oct 1996

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  • Other: DE97006804
  • Report No.: IS-M--868
  • Report No.: CONF-9610311--1
  • Grant Number: W-7405-ENG-82
  • Office of Scientific & Technical Information Report Number: 505392
  • Archival Resource Key: ark:/67531/metadc691669

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  • December 31, 1996

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

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  • Nov. 6, 2015, 8:45 p.m.

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Morris, J.R.; Deaven, D.M.; Ho, K.M.; Wang, C.Z.; Pan, B.C.; Wacker, J.G. et al. Genetic algorithm optimization of atomic clusters, article, December 31, 1996; Iowa. (digital.library.unt.edu/ark:/67531/metadc691669/: accessed July 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.