A new approach to global minimization

Aaron F. Stanton, Richard E. Bleil, Sabre Kais

Research output: Contribution to journalArticle

13 Citations (Scopus)


A new algorithm is presented for the location of the global minimum of a multiple minima problem. It begins with a series of randomly placed probes in phase space, and then uses an iterative Gaussian redistribution of the worst probes into better regions of phase space until all probes converge to a single point. The method quickly converges, does not require derivatives, and is resistant to becoming trapped in local minima. Comparison of this algorithm with others using a standard test suite demonstrates that the number of function calls has been decreased conservatively by a factor of about three with the same degree of accuracy. A sample problem of a system of seven Lennard-Jones particles is presented as a concrete example.

Original languageEnglish
Pages (from-to)594-599
Number of pages6
JournalJournal of Computational Chemistry
Issue number4
Publication statusPublished - 1 Dec 1997
Externally publishedYes


ASJC Scopus subject areas

  • Chemistry(all)
  • Safety, Risk, Reliability and Quality

Cite this

Stanton, A. F., Bleil, R. E., & Kais, S. (1997). A new approach to global minimization. Journal of Computational Chemistry, 18(4), 594-599.