Pivot method for global optimization

Pablo Serra, Aaron F. Stanton, Sabre Kais

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

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
Volume55
Issue number1 SUPPL. B
Publication statusPublished - 1 Jan 1997
Externally publishedYes

Fingerprint

pivots
Pivot
Global Optimization
Probe
optimization
probes
Phase Space
Lennard-Jones
Global Minimum
Geometric Structure
Placement
Nearest Neighbor
Extremes
High-dimensional
Choose
Entire
Converge
Series
Energy

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Mathematical Physics

Cite this

Pivot method for global optimization. / Serra, Pablo; Stanton, Aaron F.; Kais, Sabre.

In: Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, Vol. 55, No. 1 SUPPL. B, 01.01.1997, p. 1162-1165.

Research output: Contribution to journalArticle

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