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Development of a Genetic Algorithm for Optimization of Nanoalloys

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Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3103))

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Abstract

A genetic algorithm has been developed in order to find the global minimum of platinum-palladium nanoalloy clusters. The effect of biasing the initial population and predating specific clusters has been investigated.

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References

  1. Johnston, R.L.: Atomic and Molecular Clusters. Taylor & Francis, London (2002)

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  2. Johnston, R.L.: Evolving Better Nanoparticles: Genetic Algorithms for Optimising Cluster Geometries. Dalton Transactions, 4193–4207 (2003)

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  3. Massen, C., Mortimer-Jones, T.V., Johnston, R.L.: Journal of The Chemistry Society, Dalton Transactions, 4375 (2002)

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  4. Lloyd, L.D., Johnston, R.L., Salhi, S.: Theoretical Investigation of Isomer Stability in Platinum-Palladium Nanoalloy Clusters. Journal of Material Science (in press)

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  5. Cleri, F., Rosato, V.: Tight-Binding Potentials for Transition-Metals and Alloys. Physical Review B 48, 22–33 (1993)

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  6. Manby, F.R., Johnston, R.L., Roberts, C.: Predatory Genetic Algorithms. MATCH (Communications in Mathematical and Computational Chemistry) 38, 111–122 (1998)

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Author information

Authors and Affiliations

  1. School of Chemistry, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

    Lesley D. Lloyd & Roy L. Johnston

  2. School of Mathematics and Statistics, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

    Said Salhi

Authors
  1. Lesley D. Lloyd
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  2. Roy L. Johnston
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  3. Said Salhi
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Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), Kanpur, 208016, Uttar Pradesh, India

    Kalyanmoy Deb

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© 2004 Springer-Verlag Berlin Heidelberg

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Lloyd, L.D., Johnston, R.L., Salhi, S. (2004). Development of a Genetic Algorithm for Optimization of Nanoalloys. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_144

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  • DOI: https://doi.org/10.1007/978-3-540-24855-2_144

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22343-6

  • Online ISBN: 978-3-540-24855-2

  • eBook Packages: Springer Book Archive

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