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Niching strategies for particle swarm optimization
Dissertation (MS)--University of Pretoria, 2005.
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| Format: | Thesis |
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University of Pretoria
2013
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| _version_ | 1867613723921743872 |
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| access_status_str | Open Access |
| author2 | Engelbrecht, Andries P. |
| author_browse | Engelbrecht, Andries P. |
| author_facet | Engelbrecht, Andries P. |
| collection | Thesis |
| dc_rights_str_mv | © 2002, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MS)--University of Pretoria, 2005. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/30331 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:40:41.342Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/30331 Niching strategies for particle swarm optimization Engelbrecht, Andries P. rbrits@gmx.net Van den Bergh, Frans Brits, Riaan Niching Computational intelligence Particle swarm optimization (PSO) UCTD Dissertation (MS)--University of Pretoria, 2005. Evolutionary algorithms and swarm intelligence techniques have been shown to successfully solve optimization problems where the goal is to find a single optimal solution. In multimodal domains where the goal is the locate multiple solutions in a single search space, these techniques fail. Niching algorithms extend existing global optimization algorithms to locate and maintain multiple solutions concurrently. In this thesis, strategies are developed that utilize the unique characteristics of the particle swarm optimization algorithm to perform niching. Shrinking topological neighborhoods and optimization with multiple subswarms are used to identify and stably maintain niches. Solving systems of equations and multimodal functions are used to demonstrate the effectiveness of the new algorithms. Computer Science unrestricted 2013-09-07T18:48:30Z 2004-09-09 2013-09-07T18:48:30Z 2002-11-30 2005-09-09 2004-02-19 Dissertation Brits, R 2002, Niching strategies for particle swarm optimization, MS dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/30331 > http://hdl.handle.net/2263/30331 http://upetd.up.ac.za/thesis/available/etd-02192004-143003/ © 2002, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf University of Pretoria |
| spellingShingle | Niching Computational intelligence Particle swarm optimization (PSO) UCTD Niching strategies for particle swarm optimization |
| title | Niching strategies for particle swarm optimization |
| title_full | Niching strategies for particle swarm optimization |
| title_fullStr | Niching strategies for particle swarm optimization |
| title_full_unstemmed | Niching strategies for particle swarm optimization |
| title_short | Niching strategies for particle swarm optimization |
| title_sort | niching strategies for particle swarm optimization |
| topic | Niching Computational intelligence Particle swarm optimization (PSO) UCTD |
| url | http://hdl.handle.net/2263/30331 http://upetd.up.ac.za/thesis/available/etd-02192004-143003/ |