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Machine learning for global optimization

Author

Listed:
  • A. Cassioli
  • D. Di Lorenzo
  • M. Locatelli
  • F. Schoen
  • M. Sciandrone

Abstract

No abstract is available for this item.

Suggested Citation

  • A. Cassioli & D. Di Lorenzo & M. Locatelli & F. Schoen & M. Sciandrone, 2012. "Machine learning for global optimization," Computational Optimization and Applications, Springer, vol. 51(1), pages 279-303, January.
    • Handle: RePEc:spr:coopap:v:51:y:2012:i:1:p:279-303
    DOI: 10.1007/s10589-010-9330-x
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    Citations

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    Cited by:

    1. Dellepiane, Umberto & Palagi, Laura, 2015. "Using SVM to combine global heuristics for the Standard Quadratic Problem," European Journal of Operational Research, Elsevier, vol. 241(3), pages 596-605.
    2. Locatelli, Marco & Schoen, Fabio, 2012. "Local search based heuristics for global optimization: Atomic clusters and beyond," European Journal of Operational Research, Elsevier, vol. 222(1), pages 1-9.
    3. Pedro Duarte Silva, A., 2017. "Optimization approaches to Supervised Classification," European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
    4. Marco Locatelli & Fabio Schoen, 2016. "Global optimization based on local searches," Annals of Operations Research, Springer, vol. 240(1), pages 251-270, May.

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