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Conference Paper: A non-revisiting particle swarm optimization
Title | A non-revisiting particle swarm optimization |
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Authors | |
Issue Date | 2008 |
Publisher | Institute 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. 1879-1885 How to Cite? |
Abstract | In this article, a non-revisiting particle swarm optimization (NrPSO) is proposed. NrPSO is an integration of the non-revisiting scheme and a standard particle swarm optimization (PSO). It guarantees that all updated positions are not evaluated before. This property leads to two advantages: 1) it undisputedly reduces the computation cost on evaluating a time consuming and expensive objective function and 2) It helps prevent premature convergence. The non-revisiting scheme acts as a self-adaptive mutation. Particles genericly switch between local search and global search. In addition, since the adaptive mutation scheme of NrPSO involves no parameter, comparing with other variants of PSO which involve at least two performance sensitive parameters, the performance of NrPSO is more reliable. The simulation results show that NrPSO outperforms four variants of PSOs on optimizing both uni-modal and multi-modal functions with dimensions up to 40. We also illustrate that the overhead and archive size of NrPSO are insignificant. Thus NrPSO is practical for real world applications. In addition, it is shown that the performance of NrPSO is insensitive to the specific chosen values of parameters. © 2008 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/196700 |
ISBN | |
ISSN | 2023 Impact Factor: 11.7 2023 SCImago Journal Rankings: 5.209 |
DC Field | Value | Language |
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dc.contributor.author | Chow, CK | - |
dc.contributor.author | Yuen, SY | - |
dc.date.accessioned | 2014-04-24T02:10:34Z | - |
dc.date.available | 2014-04-24T02:10:34Z | - |
dc.date.issued | 2008 | - |
dc.identifier.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. 1879-1885 | - |
dc.identifier.isbn | 978-1-4244-1822-0 | - |
dc.identifier.issn | 1089-778X | - |
dc.identifier.uri | http://hdl.handle.net/10722/196700 | - |
dc.description.abstract | In this article, a non-revisiting particle swarm optimization (NrPSO) is proposed. NrPSO is an integration of the non-revisiting scheme and a standard particle swarm optimization (PSO). It guarantees that all updated positions are not evaluated before. This property leads to two advantages: 1) it undisputedly reduces the computation cost on evaluating a time consuming and expensive objective function and 2) It helps prevent premature convergence. The non-revisiting scheme acts as a self-adaptive mutation. Particles genericly switch between local search and global search. In addition, since the adaptive mutation scheme of NrPSO involves no parameter, comparing with other variants of PSO which involve at least two performance sensitive parameters, the performance of NrPSO is more reliable. The simulation results show that NrPSO outperforms four variants of PSOs on optimizing both uni-modal and multi-modal functions with dimensions up to 40. We also illustrate that the overhead and archive size of NrPSO are insignificant. Thus NrPSO is practical for real world applications. In addition, it is shown that the performance of NrPSO is insensitive to the specific chosen values of parameters. © 2008 IEEE. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4235 | - |
dc.relation.ispartof | IEEE Transactions on Evolutionary Computation | - |
dc.rights | ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.title | A non-revisiting particle swarm optimization | - |
dc.type | Conference_Paper | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/CEC.2008.4631045 | - |
dc.identifier.scopus | eid_2-s2.0-55749092762 | - |
dc.identifier.spage | 1879 | - |
dc.identifier.epage | 1885 | - |
dc.publisher.place | United States | - |
dc.customcontrol.immutable | sml 160603 amended | - |
dc.identifier.issnl | 1089-778X | - |