Challenges of continuous global optimization in molecular structure prediction Beliakov, Gleb and Lim, Kieran 2007, Challenges of continuous global optimization in molecular structure prediction, European journal of operational research, vol. 181, no. 3, pp. 1198-1213, doi: 10.1016/j.ejor.2005.08.033. Attached Files Name Description MIMEType Size Downloads beliakov_lim_EJOR.pdf Author post print application/pdf 280.80KB 449 Title Challenges of continuous global optimization in molecular structure prediction Author(s) Beliakov, Gleb orcid.org/0000-0002-9841-5292 Lim, Kieran orcid.org/0000-0001-5355-8030 Journal name European journal of operational research Volume number 181 Issue number 3 Start page 1198 End page 1213 Publisher Elsevier BV Place of publication Amsterdam, The Netherlands Publication date 2007-09-16 ISSN 0377-2217 1872-6860 Keyword(s) global optimization nonlinear programming molecular conformation branch and bound computational chemistry Summary The molecular geometry, the three dimensional arrangement of atoms in space, is a major factor determining the properties and reactivity of molecules, biomolecules and macromolecules. Computation of stable molecular conformations can be done by locating minima on the potential energy surface (PES). This is a very challenging global optimization problem because of extremely large numbers of shallow local minima and complicated landscape of PES. This paper illustrates the mathematical and computational challenges on one important instance of the problem, computation of molecular geometry of oligopeptides, and proposes the use of the Extended Cutting Angle Method (ECAM) to solve this problem. ECAM is a deterministic global optimization technique, which computes tight lower bounds on the values of the objective function and fathoms those part of the domain where the global minimum cannot reside. As with any domain partitioning scheme, its challenge is an extremely large partition of the domain required for accurate lower bounds. We address this challenge by providing an efficient combinatorial algorithm for calculating the lower bounds, and by combining ECAM with a local optimization method, while preserving the deterministic character of ECAM. Language eng DOI 10.1016/j.ejor.2005.08.033 Field of Research 010303 Optimisation HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2006, Elsevier B.V. Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30007158 Document type: Journal Article Collections: Faculty of Arts and Education Faculty of Science, Engineering and Built Environment School of Engineering and Information Technology Higher Education Research Group Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Mon, 16 Jun 2014, 08:27:51 EST Tue, 05 Dec 2017, 06:19:46 EST Fri, 07 Sep 2018, 13:44:09 EST Filtered Full Citation counts:   Cited 9 times in TR Web of Science Cited 14 times in Scopus Search Google Scholar Access Statistics: 1200 Abstract Views, 449 File Downloads  -  Detailed Statistics Created: Mon, 29 Sep 2008, 08:48:57 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.