Self-adaptive differential artificial bee colony algorithm for global optimization problems
- Submitting institution
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Glasgow Caledonian University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 33290239
- Type
- D - Journal article
- DOI
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10.1016/j.swevo.2019.01.003
- Title of journal
- Swarm and Evolutionary Computation
- Article number
- -
- First page
- 70
- Volume
- 45
- Issue
- -
- ISSN
- 2210-6502
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
-
- Supplementary information
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- 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
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2
- Research group(s)
-
-
- Citation count
- 17
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper investigates differential evolution for swarm optimisation algorithms. The paper is from the collaboration with Jiangsu University. The research builds upon the prior work on biogeography-based optimization in journal publications in Applied Soft Computing (volume 45, 2016, Elsevier) and Soft Computing (volume 21, 2017, Springer). This work was funded by the Natural Science Foundation of Jiangsu Province, China and the National Natural Science Foundation of China. The work has been extended to computationally resource constrained situation in a follow-up journal publication in Multiagent and Grid Systems (volume 16, 2020, IOS Press).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -