Pivot method for global optimization

Pablo Serra, Aaron F. Stanton, Sabre Kais

Research output: Contribution to journalArticle

35 Citations (Scopus)


A pivot algorithm for the location of a global minimum of a multiple-minimum problem is presented. The pivot method uses a series of randomly placed probes in phase space, moving the worst probes to be near better probes iteratively until the system converges. The approach chooses nearest-neighbor pivot probes to search the entire phase space by using a nonlocal distribution for the placement of the relocated probes. To test the algorithm, a standard suite of functions is given, as well as the energies and geometric structures of Lennard-Jones clusters, demonstrating the extreme efficiency of the method. Significant improvement over previous methods for high-dimensional systems is shown.

Original languageEnglish
Pages (from-to)1162-1165
Number of pages4
JournalPhysical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
Issue number1
Publication statusPublished - 1 Jan 1997


ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

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