A new approach to global minimization

✍ Scribed by Stanton, Aaron F.; Bleil, Richard E.; Kais, Sabre

• Publisher: John Wiley and Sons
• Year: 1997
• Tongue: English
• Weight: 144 KB
• Volume: 18
• Category: Article
• ISSN: 0192-8651
• DOI: 10.1002/(sici)1096-987x(199703)18:4<594::aid-jcc12>3.0.co;2-g

✦ Synopsis

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.