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Optimization of a genetic algorithm for searching molecular conformer space

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.authorBrain, Zoe E.
dc.contributor.authorAddicoat, Matthew A.
dc.date.accessioned2015-09-21T03:15:34Z
dc.date.available2015-09-21T03:15:34Z
dc.identifier.issn0021-9606
dc.identifier.urihttp://hdl.handle.net/1885/15599
dc.description.abstractWe 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.format10 pages
dc.publisherAmerican 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.sourceThe Journal of Chemical Physics
dc.subjectefficient tunings
dc.subjectmeta-genetic algorithm (GA)
dc.subjectrigid and relaxed surfaces
dc.subjectmolecular conformational search
dc.subjectevolutionary algorithm
dc.titleOptimization of a genetic algorithm for searching molecular conformer space
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume135
dcterms.dateAccepted2011-10-07
dc.date.issued2011
local.identifier.absfor080201
local.identifier.ariespublicationu4005981xPUB579
local.publisher.urlhttps://www.aip.org/
local.type.statusPublished Version
local.contributor.affiliationBrain, Zoe, College of Engineering and Computer Science, College of Engineering and Computer Science, Research School of Computer Science, The Australian National University
local.contributor.affiliationAddicoat, Matthew, College of Physical and Mathematical Sciences, CPMS Research School of Chemistry, RSC General, The Australian National University
local.identifier.essn1089-7690
local.bibliographicCitation.issue17
local.bibliographicCitation.startpage174106/1
local.bibliographicCitation.lastpage10
local.identifier.doi10.1063/1.3656323
local.identifier.absseo970108
dc.date.updated2015-12-10T08:11:14Z
local.identifier.scopusID2-s2.0-80855139855
local.identifier.thomsonID000296733300006
CollectionsANU Research Publications

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