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Global minimum structure searches via particle swarm optimization
Author(s) -
Call Seth T.,
Zubarev Dmitry Yu.,
Boldyrev Alexander I.
Publication year - 2007
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/jcc.20621
Subject(s) - particle swarm optimization , simulated annealing , convergence (economics) , mathematical optimization , hydroxide , hydride , genetic algorithm , global optimization , computer science , software , population , metaheuristic , algorithm , materials science , mathematics , engineering , chemical engineering , metal , demography , sociology , economics , metallurgy , programming language , economic growth
Abstract Novel implementation of the evolutionary approach known as particle swarm optimization (PSO) capable of finding the global minimum of the potential energy surface of atomic assemblies is reported. This is the first time the PSO technique has been used to perform global optimization of minimum structure search for chemical systems. Significant improvements have been introduced to the original PSO algorithm to increase its efficiency and reliability and adapt it to chemical systems. The developed software has successfully found the lowest‐energy structures of the LJ 26 Lennard‐Jones cluster, anionic silicon hydride Si 2 H 5 − , and triply hydrated hydroxide ion OH − (H 2 O) 3 . It requires relatively small population sizes and demonstrates fast convergence. Efficiency of PSO has been compared with simulated annealing, and the gradient embedded genetic algorithm. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007