Impact of communication topology in particle_x000D_
swarm optimization
- Submitting institution
-
Goldsmiths' College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2815
- Type
- D - Journal article
- DOI
-
10.1109/TEVC.2018.2880894
- Title of journal
- IEEE Transactions on Evolutionary Computation
- Article number
- -
- First page
- 689
- Volume
- 23
- Issue
- 4
- ISSN
- 1089-778X
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2018
- URL
-
http://research.gold.ac.uk/id/eprint/25050/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Particle Swarm Optimization, a highly studied and applied (mentioned in over 400,000 publications) local optimiser, exists in two forms: local and global. This paper is significant because it establishes, through trials on a bespoke testbed assembled from several standard benchmarks, that the local form is superior for all but the simplest type of problem. The study addresses the omission of the local form in recent work. Furthermore, the paper introduces two new measures: last significant improvement as a refined measure of algorithm stagnation and mobility, a quantification of algorithm ability to jump between optima.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -