Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
The perils of particle swarm optimization in high dimensional problem spaces
Dissertation (MSc)--University of Pretoria, 2017.
Saved in:
| Other Authors: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
University of Pretoria
2018
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613486065909760 |
|---|---|
| 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 | © 2018 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 (MSc)--University of Pretoria, 2017. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/66233 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:36:54.588Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| 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:2263/66233 The perils of particle swarm optimization in high dimensional problem spaces Engelbrecht, Andries P. u11081092@tuks.co.za Cleghorn, Christopher Wesley Oldewage, Elre Talea UCTD Particle swarm optimization (PSO) High dimensions Large scale optimisation Engineering, built environment and information technology theses SDG-04 Engineering, built environment and information technology theses SDG-09 Dissertation (MSc)--University of Pretoria, 2017. Particle swarm optimisation (PSO) is a stochastic, population-based optimisation algorithm. PSO has been applied successfully to a variety of domains. This thesis examines the behaviour of PSO when applied to high dimensional optimisation problems. Empirical experiments are used to illustrate the problems exhibited by the swarm, namely that the particles are prone to leaving the search space and never returning. This thesis does not intend to develop a new version of PSO speci cally for high dimensional problems. Instead, the thesis investigates why PSO fails in high dimensional search spaces. Four di erent types of approaches are examined. The rst is the application of velocity clamping to prevent the initial velocity explosion and to keep particles inside the search space. The second approach selects values for the acceleration coe cients and inertia weights so that particle movement is restrained or so that the swarm follows particular patterns of movement. The third introduces coupling between problem variables, thereby reducing the swarm's movement freedom and forcing the swarm to focus more on certain subspaces within the search space. The nal approach examines the importance of initialisation strategies in controlling the swarm's exploration to exploitation ratio. The thesis shows that the problems exhibited by PSO in high dimensions, particularly unwanted particle roaming, can not be fully mitigated by any of the techniques examined. The thesis provides deeper insight into the reasons for PSO's poor performance by means of extensive empirical tests and theoretical reasoning. bs2026 Computer Science MSc Unrestricted SDG-04: Quality education SDG-09: Industry, innovation and infrastructure 2018-08-17T09:42:45Z 2018-08-17T09:42:45Z 2005/02/18 2017 Dissertation Oldewage, ET 2017, The perils of particle swarm optimization in high dimensional problem spaces, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/66233> A2018 http://hdl.handle.net/2263/66233 en © 2018 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 University of Pretoria |
| spellingShingle | UCTD Particle swarm optimization (PSO) High dimensions Large scale optimisation Engineering, built environment and information technology theses SDG-04 Engineering, built environment and information technology theses SDG-09 The perils of particle swarm optimization in high dimensional problem spaces |
| title | The perils of particle swarm optimization in high dimensional problem spaces |
| title_full | The perils of particle swarm optimization in high dimensional problem spaces |
| title_fullStr | The perils of particle swarm optimization in high dimensional problem spaces |
| title_full_unstemmed | The perils of particle swarm optimization in high dimensional problem spaces |
| title_short | The perils of particle swarm optimization in high dimensional problem spaces |
| title_sort | perils of particle swarm optimization in high dimensional problem spaces |
| topic | UCTD Particle swarm optimization (PSO) High dimensions Large scale optimisation Engineering, built environment and information technology theses SDG-04 Engineering, built environment and information technology theses SDG-09 |
| url | http://hdl.handle.net/2263/66233 |