Optimization of a genetic algorithm for searching molecular conformer space
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Brain, Zoe E.; Addicoat, Matthew A.
Description
We present two sets of tunings that are broadly applicable to conformer searches of isolated molecules using a genetic algorithm (GA). In order to find the most efficient tunings for the GA, a second GA-- a meta-genetic algorithm--was used to tune the first genetic algorithm to reliably find the already known a priori correct answer with minimum computational resources. It is shown that these tunings are appropriate for a variety of molecules with different characteristics, and most importantly...[Show more]
dc.contributor.author | Brain, Zoe E. | |
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dc.contributor.author | Addicoat, Matthew A. | |
dc.date.accessioned | 2015-09-21T03:15:34Z | |
dc.date.available | 2015-09-21T03:15:34Z | |
dc.identifier.issn | 0021-9606 | |
dc.identifier.uri | http://hdl.handle.net/1885/15599 | |
dc.description.abstract | We present two sets of tunings that are broadly applicable to conformer searches of isolated molecules using a genetic algorithm (GA). In order to find the most efficient tunings for the GA, a second GA-- a meta-genetic algorithm--was used to tune the first genetic algorithm to reliably find the already known a priori correct answer with minimum computational resources. It is shown that these tunings are appropriate for a variety of molecules with different characteristics, and most importantly that the tunings are independent of the underlying model chemistry but that the tunings for rigid and relaxed surfaces differ slightly. It is shown that for the problem of molecular conformational search, the most efficient GA actually reduces to an evolutionary algorithm. | |
dc.format | 10 pages | |
dc.publisher | American Institute of Physics (AIP) | |
dc.rights | © 2011 American Institute of Physics http://www.sherpa.ac.uk/romeo/issn/0021-9606 Publishers version/PDF may be used on author's personal website, institutional website or institutional repository (Sherpa/Romeo as of 21/9/2015). http://publishing.aip.org/authors/web-posting-guidelines Copyright 2011 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Journal of Chemical Physics and may be found at http://doi.org/10.1063/1.3656323 (Publisher's journal site as of 21/9/2015). | |
dc.source | The Journal of Chemical Physics | |
dc.subject | efficient tunings | |
dc.subject | meta-genetic algorithm (GA) | |
dc.subject | rigid and relaxed surfaces | |
dc.subject | molecular conformational search | |
dc.subject | evolutionary algorithm | |
dc.title | Optimization of a genetic algorithm for searching molecular conformer space | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 135 | |
dcterms.dateAccepted | 2011-10-07 | |
dc.date.issued | 2011 | |
local.identifier.absfor | 080201 | |
local.identifier.ariespublication | u4005981xPUB579 | |
local.publisher.url | https://www.aip.org/ | |
local.type.status | Published Version | |
local.contributor.affiliation | Brain, Zoe, College of Engineering and Computer Science, College of Engineering and Computer Science, Research School of Computer Science, The Australian National University | |
local.contributor.affiliation | Addicoat, Matthew, College of Physical and Mathematical Sciences, CPMS Research School of Chemistry, RSC General, The Australian National University | |
local.identifier.essn | 1089-7690 | |
local.bibliographicCitation.issue | 17 | |
local.bibliographicCitation.startpage | 174106/1 | |
local.bibliographicCitation.lastpage | 10 | |
local.identifier.doi | 10.1063/1.3656323 | |
local.identifier.absseo | 970108 | |
dc.date.updated | 2015-12-10T08:11:14Z | |
local.identifier.scopusID | 2-s2.0-80855139855 | |
local.identifier.thomsonID | 000296733300006 | |
Collections | ANU Research Publications |
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01_Brain_Optimization_of_a_genetic_2011.pdf | Published Version | 1.2 MB | Adobe PDF |
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