An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition
- Submitting institution
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University of Exeter
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1784
- Type
- D - Journal article
- DOI
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10.1109/TEVC.2014.2373386
- Title of journal
- IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
- Article number
- -
- First page
- 694
- Volume
- 19
- Issue
- 5
- ISSN
- 1089-778X
- Open access status
- Out of scope for open access requirements
- Month of publication
- November
- Year of publication
- 2014
- URL
-
-
- 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
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3
- Research group(s)
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-
- Citation count
- 425
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper pioneered investigations into the complementary effect of Pareto- and decomposition-based selection mechanisms and has been recognized as the state-of-the-art in an IEEE Computational Intelligence Society award-winning paper (DOI: 10.1109/TEVC.2016.2587749). The work has been highly cited and inspired many others, e.g., DOI: 10.1109/TEVC.2016.2519378 which is thereafter highly cited too. It has been widely used as a baseline benchmark algorithm in evolutionary many-objective optimisation research field. It has been integrated into PlatEMO, an IEEE Computational Intelligence Society award-winning paper (DOI: 10.1109/MCI.2017.2742868) and a popular open-source evolutionary multi-objective optimisation algorithm packages with more than 400 stars and 200 forks in GitHub.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -