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Global cluster geometry optimization by a phenotype algorithm with Niches: Location of elusive minima, and low‐order scaling with cluster size
Author(s) -
Hartke Bernd
Publication year - 1999
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/(sici)1096-987x(199912)20:16<1752::aid-jcc7>3.0.co;2-0
Subject(s) - maxima and minima , cluster (spacecraft) , benchmark (surveying) , scaling , global optimization , algorithm , computer science , maxima , statistical physics , geometry , physics , mathematics , mathematical analysis , geography , geodesy , programming language , art , performance art , art history
The problem of global geometry optimization of clusters is addressed with a phenotype variant of the method of genetic algorithms, with several novel performance enhancements. The resulting algorithm is applied to Lennard–Jones clusters as benchmark system, with up to 150 atoms. The well‐known, difficult cases involving nonicosahedral global minima can be treated reliably using the concept of niches. The scaling of computer time with cluster size is approximately cubic, which is crucial for future applications to much larger clusters. © 1999 John Wiley & Sons, Inc. J Comput Chem 20: 1752–1759, 1999