A multiobjective state transition algorithm for single machine scheduling Zhou, Xiaojun, Hanoun, Samer, Gao, David Yang and Nahavandi, Saeid 2015, A multiobjective state transition algorithm for single machine scheduling, in ICONIP 2015 : Proceedings of the 22nd International Conference on Neural Information Processing, Springer, New York, N.Y., pp. 79-88, doi: 10.1007/978-3-319-08377-3_9. Attached Files Name Description MIMEType Size Downloads Title A multiobjective state transition algorithm for single machine scheduling Author(s) Zhou, Xiaojun Hanoun, Samer orcid.org/0000-0002-8697-1515 Gao, David Yang Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Conference name Neural Information Processing International Conference ( 22nd : 2015 : Istanbul, Turkey) Conference location Istanbul, Turkey Conference dates 9-12 Nov. 2015 Title of proceedings ICONIP 2015 : Proceedings of the 22nd International Conference on Neural Information Processing Publication date 2015 Series Springer Proceedings in Mathematics and Statistics v.95 Start page 79 End page 88 Total pages 10 Publisher Springer Place of publication New York, N.Y. Keyword(s) Science & Technology Physical Sciences Mathematics Statistics & Probability Discrete state transition algorithm Multiobjective optimization Single machine scheduling OPTIMIZATION Summary In this paper, a discrete state transition algorithm is introduced to solve a multiobjective single machine job shop scheduling problem. In the proposed approach, a non-dominated sort technique is used to select the best from a candidate state set, and a Pareto archived strategy is adopted to keep all the non-dominated solutions. Compared with the enumeration and other heuristics, experimental results have demonstrated the effectiveness of the multiobjective state transition algorithm. ISBN 9783319083766 ISSN 2194-1009 2194-1017 Language eng DOI 10.1007/978-3-319-08377-3_9 Field of Research 010303 Optimisation 091099 Manufacturing Engineering not elsewhere classified Socio Economic Objective 970109 Expanding Knowledge in Engineering HERDC Research category E1 Full written paper - refereed ERA Research output type E Conference publication Copyright notice ©2015, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30076653 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research Related Links Link Description Connect to published version 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. Versions Version Filter Type Tue, 25 Aug 2015, 14:41:38 EST Wed, 26 Aug 2015, 05:05:36 EST Wed, 26 Aug 2015, 08:14:58 EST Wed, 26 Aug 2015, 08:21:12 EST Mon, 19 Oct 2015, 12:29:41 EST Mon, 18 Jan 2016, 07:28:06 EST Tue, 26 Apr 2016, 09:47:48 EST Wed, 27 Apr 2016, 06:06:58 EST Tue, 17 May 2016, 12:58:13 EST Tue, 17 May 2016, 13:00:47 EST Filtered Full Citation counts:   Cited 5 times in TR Web of Science Cited 6 times in Scopus Search Google Scholar Access Statistics: 513 Abstract Views, 3 File Downloads  -  Detailed Statistics Created: Tue, 26 Apr 2016, 09:47:48 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.