Application of cuckoo search for design optimization of heat exchangers Khosravi, Rihanna, Khosravi, Abbas and Nahavandi, Saeid 2014, Application of cuckoo search for design optimization of heat exchangers. In Loo, C. K., Yap, K. S., Wong, K. W., Teoh, A. and Huang, K. (ed), Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part II, Springer, Cham, Switzerland, pp.178-185, doi: 10.1007/978-3-319-12640-1. Attached Files Name Description MIMEType Size Downloads Title Application of cuckoo search for design optimization of heat exchangers Author(s) Khosravi, Rihanna Khosravi, Abbas orcid.org/0000-0001-6927-0744 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Title of book Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part II Editor(s) Loo, C. K. Yap, K. S. Wong, K. W. Teoh, A. Huang, K. Publication date 2014 Series Lecture notes in computer science; v.8835 Chapter number 22 Total chapters 71 Start page 178 End page 185 Total pages 8 Publisher Springer Place of Publication Cham, Switzerland Keyword(s) Cuckoo search Genetic algorithm Heat exchanger Optimization Summary A wide variety of evolutionary optimization algorithms have been used by researcher for optimal design of shell and tube heat exchangers (STHX). The purpose of optimization is to minimize capital and operational costs subject to efficiency constraints. This paper comprehensively examines performance of genetic algorithm (GA) and cuckoo search (CS) for solving STHX design optimization. While GA has been widely adopted in the last decade for STHX optimal design, there is no report on application of CS method for this purpose. Simulation results in this paper demonstrate that CS greatly outperforms GA in terms of finding admissible and optimal configurations for STHX. It is also found that CS method not only has a lower computational requirement, but also generates the most consistent results. ISBN 9783319126395 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-319-12640-1 Field of Research 080108 Neural, Evolutionary and Fuzzy Computation Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category B1 Book chapter ERA Research output type B Book chapter Copyright notice ©2014, Springer International Publishing Persistent URL http://hdl.handle.net/10536/DRO/DU:30070734 Document type: Book Chapter 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 Mon, 16 Mar 2015, 14:48:36 EST Tue, 17 Mar 2015, 04:05:38 EST Thu, 30 Apr 2015, 16:03:58 EST Thu, 07 May 2015, 06:06:03 EST Thu, 07 May 2015, 11:39:06 EST Thu, 07 May 2015, 11:41:27 EST Thu, 07 May 2015, 11:42:23 EST Tue, 19 May 2015, 14:16:35 EST Fri, 12 Jun 2015, 13:37:39 EST Wed, 21 Dec 2016, 13:39:29 EST Sat, 09 Jun 2018, 02:30:39 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 572 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Thu, 30 Apr 2015, 16:03:58 EST

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