File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: A non-revisiting simulated annealing algorithm

TitleA non-revisiting simulated annealing algorithm
Authors
Issue Date2008
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4235
Citation
The 2008 IEEE Congress on Evolutionary Computation (CEC 2008), Hong Kong, China, 1-6 June 2008. In IEEE Transactions on Evolutionary Computation, 2008, p. 1886-1892 How to Cite?
AbstractIn this article, a non-revisiting simulated annealing algorithm (NrSA) is proposed. NrSA is an integration of the non-revisiting scheme and standard simulated annealing (SA). It guarantees that every generated neighbor must not be visited before. This property leads to reduction on the computation cost on evaluating time consuming and expensive objective functions such as surface registration, optimized design and energy management of heating, ventilating and air conditioning systems. Meanwhile, the prevention on function re-evaluation also speeds up the convergence. Furthermore, due to the nature of the non-revisiting scheme, the returned non-revisited solutions from the scheme can be treated as self-adaptive solutions, such that no parametric neighbor picking scheme is involved in NrSA. Thus NrSA can be identified as a parameter-less SA. The simulation results show that NrSA is superior to adaptive SA (ASA) on both uni-modal and multi-modal functions with dimension up to 40. We also illustrate that the overhead and archive size of NrSA are insignificant, so it is practical for real world applications. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/196703
ISBN
ISSN
2015 Impact Factor: 5.908
2015 SCImago Journal Rankings: 4.308

 

DC FieldValueLanguage
dc.contributor.authorYuen, SY-
dc.contributor.authorChow, CK-
dc.date.accessioned2014-04-24T02:10:35Z-
dc.date.available2014-04-24T02:10:35Z-
dc.date.issued2008-
dc.identifier.citationThe 2008 IEEE Congress on Evolutionary Computation (CEC 2008), Hong Kong, China, 1-6 June 2008. In IEEE Transactions on Evolutionary Computation, 2008, p. 1886-1892-
dc.identifier.isbn978-1-4244-1822-0-
dc.identifier.issn1089-778X-
dc.identifier.urihttp://hdl.handle.net/10722/196703-
dc.description.abstractIn this article, a non-revisiting simulated annealing algorithm (NrSA) is proposed. NrSA is an integration of the non-revisiting scheme and standard simulated annealing (SA). It guarantees that every generated neighbor must not be visited before. This property leads to reduction on the computation cost on evaluating time consuming and expensive objective functions such as surface registration, optimized design and energy management of heating, ventilating and air conditioning systems. Meanwhile, the prevention on function re-evaluation also speeds up the convergence. Furthermore, due to the nature of the non-revisiting scheme, the returned non-revisited solutions from the scheme can be treated as self-adaptive solutions, such that no parametric neighbor picking scheme is involved in NrSA. Thus NrSA can be identified as a parameter-less SA. The simulation results show that NrSA is superior to adaptive SA (ASA) on both uni-modal and multi-modal functions with dimension up to 40. We also illustrate that the overhead and archive size of NrSA are insignificant, so it is practical for real world applications. © 2008 IEEE.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4235-
dc.relation.ispartofIEEE Transactions on Evolutionary Computation-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsIEEE Transactions on Evolutionary Computation. Copyright © Institute of Electrical and Electronics Engineers.-
dc.titleA non-revisiting simulated annealing algorithm-
dc.typeConference_Paper-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/CEC.2008.4631046-
dc.identifier.scopuseid_2-s2.0-55749101909-
dc.identifier.spage1886-
dc.identifier.epage1892-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 160602 amended-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats