Particle Swarm Optimisation with Improved Learning Strategy
In this paper, a new variant of particle swarm optimisation (PSO) called PSO with improved learning strategy (PSO-ILS) is developed. Specifically, an ILS module is proposed to generate a more effective and efficient exemplar, which could offer a more promising search direction to the PSO-ILS part...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor's University
2015
|
| Subjects: | |
| Online Access: | http://eprints.usm.my/42783/ http://eprints.usm.my/42783/1/JES_Vol._11_2015_-_Art._4%2827-48%29.pdf |
| _version_ | 1848879655290929152 |
|---|---|
| author | Wei , Hong Lim Isa, Nor Ashidi Mat |
| author_facet | Wei , Hong Lim Isa, Nor Ashidi Mat |
| author_sort | Wei , Hong Lim |
| building | USM Institutional Repository |
| collection | Online Access |
| description | In this paper, a new variant of particle swarm optimisation (PSO) called PSO
with improved learning strategy (PSO-ILS) is developed. Specifically, an ILS module is
proposed to generate a more effective and efficient exemplar, which could offer a more
promising search direction to the PSO-ILS particle. Comparison is made on the PSO-ILS
with 6 well-established PSO variants on 10 benchmark functions to investigate the
optimisation capability of the proposed algorithm. The simulation results reveal that
PSO-ILS outperforms its peers for the majority of the tested benchmarks by
demonstrating superior search accuracy, reliability and efficiency. |
| first_indexed | 2025-11-15T17:50:41Z |
| format | Article |
| id | usm-42783 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:50:41Z |
| publishDate | 2015 |
| publisher | Taylor's University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-427832018-10-30T01:37:12Z http://eprints.usm.my/42783/ Particle Swarm Optimisation with Improved Learning Strategy Wei , Hong Lim Isa, Nor Ashidi Mat TA1-2040 Engineering (General). Civil engineering (General) In this paper, a new variant of particle swarm optimisation (PSO) called PSO with improved learning strategy (PSO-ILS) is developed. Specifically, an ILS module is proposed to generate a more effective and efficient exemplar, which could offer a more promising search direction to the PSO-ILS particle. Comparison is made on the PSO-ILS with 6 well-established PSO variants on 10 benchmark functions to investigate the optimisation capability of the proposed algorithm. The simulation results reveal that PSO-ILS outperforms its peers for the majority of the tested benchmarks by demonstrating superior search accuracy, reliability and efficiency. Taylor's University 2015 Article PeerReviewed application/pdf en http://eprints.usm.my/42783/1/JES_Vol._11_2015_-_Art._4%2827-48%29.pdf Wei , Hong Lim and Isa, Nor Ashidi Mat (2015) Particle Swarm Optimisation with Improved Learning Strategy. Journal of Engineering Science and Technology, 11. pp. 27-48. ISSN 1823-4690 http://web.usm.my/jes/11_2015/JES%20Vol.%2011%202015%20-%20Art.%204(27-48).pdf |
| spellingShingle | TA1-2040 Engineering (General). Civil engineering (General) Wei , Hong Lim Isa, Nor Ashidi Mat Particle Swarm Optimisation with Improved Learning Strategy |
| title | Particle Swarm Optimisation with Improved Learning Strategy |
| title_full | Particle Swarm Optimisation with Improved Learning Strategy |
| title_fullStr | Particle Swarm Optimisation with Improved Learning Strategy |
| title_full_unstemmed | Particle Swarm Optimisation with Improved Learning Strategy |
| title_short | Particle Swarm Optimisation with Improved Learning Strategy |
| title_sort | particle swarm optimisation with improved learning strategy |
| topic | TA1-2040 Engineering (General). Civil engineering (General) |
| url | http://eprints.usm.my/42783/ http://eprints.usm.my/42783/ http://eprints.usm.my/42783/1/JES_Vol._11_2015_-_Art._4%2827-48%29.pdf |